University of Tennessee, Knoxville University of Tennessee, Knoxville

TRACE: Tennessee Research and Creative TRACE: Tennessee Research and Creative

Exchange Exchange

Masters Theses Graduate School

8-2016

Role of Sorting on the Composition of Siliciclastic Sediment: Role of Sorting on the Composition of Siliciclastic Sediment:

Implications for Interpreting Provenance after Limited Transport Implications for Interpreting Provenance after Limited Transport

in an Arid Climate in an Arid Climate

Forrest Christopher Driscoll University of Tennessee, Knoxville, fdriscol@vols.utk.edu

Follow this and additional works at: https://trace.tennessee.edu/utk_gradthes

Part of the Geochemistry Commons, Geology Commons, and the Sedimentology Commons

Recommended Citation Recommended Citation Driscoll, Forrest Christopher, "Role of Sorting on the Composition of Siliciclastic Sediment: Implications for Interpreting Provenance after Limited Transport in an Arid Climate. " Master's Thesis, University of Tennessee, 2016. https://trace.tennessee.edu/utk_gradthes/4032

This Thesis is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Masters Theses by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact trace@utk.edu.

To the Graduate Council:

I am submitting herewith a thesis written by Forrest Christopher Driscoll entitled "Role of Sorting

on the Composition of Siliciclastic Sediment: Implications for Interpreting Provenance after

Limited Transport in an Arid Climate." I have examined the final electronic copy of this thesis for

form and content and recommend that it be accepted in partial fulfillment of the requirements

for the degree of Master of Science, with a major in Geology.

Christopher M. Fedo, Major Professor

We have read this thesis and recommend its acceptance:

Annette S. Engel, Robert D. Hatcher

Accepted for the Council:

Carolyn R. Hodges

Vice Provost and Dean of the Graduate School

(Original signatures are on file with official student records.)

Role of Sorting on the Composition of Siliciclastic

Sediment: Implications for Interpreting Provenance

after Limited Transport in an Arid Climate

A Thesis Presented for the

Master of Science

Degree

The University of Tennessee, Knoxville

Forrest Christopher Driscoll

August 2016

ii

Copyright © 2016 by Forrest Christopher Driscoll

All rights reserved.

iii

ACKNOWLEDGEMENTS

Completion of this work was made possible through the assistance of many

people. Dr. Chris Fedo provided constant guidance, feedback, and fruitful discussion as

an advisor. Committee members Dr. Bob Hatcher and Dr. Annette Engel helped to

review my work and progress. Drs. Scott Samson and Mariana Bonich helped during a

field season in the Mojave Desert by providing on-site discussion. Dr. Jeff Moersch

operated the drone used to obtain high resolution aerial photographs of the field site.

Graduate students at the University of Tennessee, friends, and family offered tremendous

guidance and support during the completion of my degree. A grant awarded from the

Geological Society of America was used to fund the petrography, geochemistry, and

travel expenses for this study.

iv

ABSTRACT

This study tested whether transport distances (< 500 m) have the capacity to shape

the geochemistry of sediments across multiple grain-size populations due to sorting

derived from a single source. In the Stepladder Mountains, Mojave Desert, CA, a < 1 km2

[square kilometers] watershed allows for a controlled study to understand how modern

sediments acquire their composition from a single granodioritic source in an arid climate

where there is no chemical weathering. Sediments are naturally sorted into distinct grain-

size populations, with modes ranging from very fine sand to gravel within a single,

alluvial channel. Sediment samples representative of each population were

petrographically and geochemically analyzed in order to test the effectiveness of

commonly used discrimination diagrams. Sediments became proportionally enriched in

plagioclase and biotite and depleted in K-feldspar and quartz with decreasing grain size.

Major elements were plotted in Al2O3 [aluminum oxide]–CaO*+Na2O [sodium oxide]–

K2O [potassium oxide] and Al2O3–CaO*+Na2O+K2O–FeO+MgO compositional space

and indicate that a negligible degree of chemical weathering was involved in sediment

production. Trace-element plots normalized to average granodiorite bedrock show strong

enrichments in elements thought to be immobile during sedimentary processing (Cr, Co,

and Sc) across nearly all sediment samples. Using any of these elements as ratios (Th/Co,

La/Sc, Th/Sc, Cr/Th, Zr/Sc) in provenance discriminating plots reveal that sediment was

formed source mixing, as sediments in these plots considerably deviate from bedrock

composition due to the control grain size has on geochemistry. Sediment rare-earth

element (REE) contents also deviate from source composition and show an increase in

total REE content, decrease in fractionation of light REEs and heavy REEs, and an

v

increase in the magnitude of the negative Eu anomaly with decreasing grain size.

Variations in sediment composition and thus geochemical ratios result from mineral

sorting during transport, no matter how short. Thus, strong caution must be used when

using discrimination diagrams to interpret sediment and sedimentary rock provenance.

vi

TABLE OF CONTENTS

1. INTRODUCTION .......................................................................................................... 1 2. GEOLOGIC SETTING .................................................................................................. 9 3. CHARACTERIZATION OF WATERSHED .............................................................. 11

4. METHODS ................................................................................................................... 13 4.1 Field Work .............................................................................................................. 13 4.2 Textural Analysis and Sample Preparation ............................................................. 13 4.3 Petrography ............................................................................................................. 16 4.4 Geochemical analysis.............................................................................................. 16

5. ANALYSIS OF STEPLADDER BEDROCK AND SAPROLITE .............................. 21 5.1 Stepladder Bedrock ................................................................................................. 21

5.1.1 Petrology .......................................................................................................... 21 5.1.2 Geochemistry ................................................................................................... 23

5.1.2.1 Major Elements ......................................................................................... 23 5.1.2.2 Trace- and rare-earth elements ................................................................ 24

5.2 Stepladder Saprolite ................................................................................................ 27 5.2.1 Petrology .......................................................................................................... 27 5.2.2 Geochemistry ................................................................................................... 30

5.2.2.1 Major elements.......................................................................................... 30 5.2.2.2 Trace- and rare-earth elements ................................................................ 31

5.3 Joint Sets ................................................................................................................. 31 6. ANALYSIS OF STEPLADDER SEDIMENT ............................................................. 33

6.1 Textural analysis ..................................................................................................... 33

6.1.1 CD-1 ................................................................................................................. 33

6.1.2 CD-2 ................................................................................................................. 33 6.1.3 CD-3 ................................................................................................................. 36 6.1.4 CD-4 ................................................................................................................. 36

6.1.5 CD-5 ................................................................................................................. 36 6.1.6 CD-M ............................................................................................................... 37

6.2 Petrography ............................................................................................................. 37 6.2.1 Quartz ............................................................................................................... 39 6.2.2 Plagioclase ....................................................................................................... 39 6.2.3 K-feldspar ........................................................................................................ 40

6.2.4 Biotite ............................................................................................................... 40 6.2.5 Accessory phases ............................................................................................. 41

6.3 Geochemistry .......................................................................................................... 41

6.3.1 Major elements................................................................................................. 41 6.3.2 Trace-elements ................................................................................................. 41 6.3.3 Rare-earth elements ......................................................................................... 42

7. EVALUATION OF THE PROCESSES AFFECTING SEDIMENT

GEOCHEMISTRY ........................................................................................................... 45 7.1 Chemical Weathering.............................................................................................. 45 7.2 Physical Sorting ...................................................................................................... 48

vii

8. EVALUATION OF THE UTILITY OF PROVENANCE INDICATORS .................. 49 8.1 Major elements........................................................................................................ 49

8.1.1 A–CN–K and A–CNK–FM diagrams .............................................................. 49 8.1.2 Discriminant function plots.............................................................................. 50

8.2 Trace elements ........................................................................................................ 52 8.2.1 Incompatible to compatible element ratio plots ............................................... 52 8.2.2 Sediment recycling ratio plots ......................................................................... 57

8.3 Rare-earth elements ................................................................................................ 60 8.3.1 Rare-earth element plots .................................................................................. 61

8.3.1.1 Total REE content ..................................................................................... 61 8.3.1.2 Europium anomaly .................................................................................... 61 8.3.1.3 LREE and HREE content .......................................................................... 63

9. SUMMARY AND CONCLUSIONS ........................................................................... 65

REFERENCES CITED ..................................................................................................... 68 APPENDICES .................................................................................................................. 78

Appendix A ................................................................................................................... 79 Appendix B ................................................................................................................... 94

Appendix C ................................................................................................................... 96 Appendix D ................................................................................................................. 101

VITA ............................................................................................................................... 107

viii

LIST OF TABLES

Table 1. Textural descriptions and data for Stepladder sediments ................................... 15 Table 2. Point-counted mineralogical modes of Stepladder samples ............................... 17 Table 3. Major element oxide contents of Stepladder samples. ....................................... 18 Table 4. Trace and rare-earth element contents of Stepladder samples ............................ 19

Table 5. Rare-earth element ratios of Stepladder samples. ............................................... 28

Table B 1. Measurements of joint set orientations across watershed. .............................. 95

Table C 1. Sieve data for each sediment sample. ............................................................. 99

Table C 2. Textural data output from GRADISTAT program. ...................................... 100

Table D 1. Descriptive compositional parameters and ratios. ........................................ 105 Table D 2. Trace element ratios. ..................................................................................... 106

ix

LIST OF FIGURES

Figure 1. Map of the field area in the Mojave Desert, southeastern CA.. .......................... 4

Figure 2. Oblique aerial image of studied watershed in the Stepladder Mountains, CA .... 7 Figure 3. Channel section holding sorted Stepladder sediments ........................................ 8 Figure 4. Images of sediment samples collected from the channel section. ..................... 14 Figure 5. Bedrock field and hand sample photographs and photomicrographs ................ 22 Figure 6. Geochemical discriminatory plots for Stepladder bedrock and saprolite .......... 25

Figure 7. Bedrock and saprolite trace and rare-earth element spider-plots ...................... 26 Figure 8. Saprolite field and hand sample photographs and photomicrographs ............... 29 Figure 9. Fracture system field photographs and joint orientations.................................. 32 Figure 10. Frequency percent distribution curves of collected sediment samples. .......... 34 Figure 11. Stepladder sediment sample photomicrographs .............................................. 35

Figure 12. QPK, QFB, and QFL plots of Stepladder sediments ....................................... 38 Figure 13. Trace and rare-earth element spider-plots ....................................................... 44

Figure 14. A-CN-K and A-CNK-FM compositional plots for the average Stepladder

bedrock, saprolite, and channel section sediments.. ................................................. 46

Figure 15. Discriminant function provenance plots .......................................................... 51 Figure 16. Incompatible to compatible immobile trace element provenance plots .......... 54 Figure 17. Trace element plots indicating extent of sediment recycling .......................... 58

Figure 18. Bedrock-normalized Eu/Eu* plots.. ................................................................ 62

Figure A 1. Photomicrographs of Stepladder bedrock. ..................................................... 80 Figure A 2. Photomicrographs of Stepladder saprolite. .................................................... 81 Figure A 3. Loose sediment from sample CD-1. .............................................................. 82

Figure A 4. Photomicrographs of sample CD-1. .............................................................. 83

Figure A 5. Loose sediment from sample CD-2. .............................................................. 84 Figure A 6. Photomicrographs of sample CD-2. .............................................................. 85 Figure A 7. Loose sediment from sample CD-3. .............................................................. 86

Figure A 8. Photomicrographs of sample CD-3. .............................................................. 87 Figure A 9. Loose sediment from sample CD-4. .............................................................. 88 Figure A 10. Photomicrographs of sample CD-4. ............................................................ 89

Figure A 11. Loose sediment from sample CD-5. ............................................................ 90 Figure A 12. Photomicrographs of sample CD-5. ............................................................ 91 Figure A 13. Field photographs of sample CD-M in channel........................................... 92 Figure A 14. Loose sediment from sample CD-M. .......................................................... 93

Figure C 1. Grain-size overlays of samples CD-1 and CD-3 with samples from Modi

(2011) with similar grain-size distributions. ............................................................. 97

Figure C 2. Gravel-Mud-Sand textural classification diagram. ........................................ 98

Figure D 1. Quartz-Alkali feldspar-Plagioclase (QAP) classification diagram. ............. 102 Figure D 2. Elemental abundances of Cr, Sc, Co, and FeO across average bedrock and

channel sediments. .................................................................................................. 103 Figure D 3. Cr/Th vs Th/Sc iterative plots of samples CD-1 and CD-3. ........................ 104

1

1. INTRODUCTION

Unravelling the petrologic origin of sediment requires an approach that addresses

the processes that control detrital composition from source to sink. Beyond original

provenance compositions, sedimentary processes, such as chemical weathering, source

mixing, mineral sorting during transport, and diagenesis, are all capable of affecting the

composition of sediment after being released from source (Johnsson, 1993). Thus, the

ability to reconstruct provenance (i.e., deciphering source rock characteristics from

sediment) is limited to how well each step is understood.

For decades, numerous studies have used petrography and geochemistry as a way

to reconstruct sediment provenance under the premise that source is the dominant control

on sediment composition. Petrographic applications used the mineralogical modes to

interpret tectonic settings of source terrains (Dickinson, 1970; Dickinson and Suczek,

1979; Dickinson and Valloni, 1980; Bhatia, 1983; Dickinson et al., 1983; Ingersoll et al.,

1984) and to decipher paleoclimates (Basu, 1976; Suttner et al., 1981; Basu, 1985). With

the advent of methods capable of extracting whole-rock geochemical information, major

oxides have been used to observe the relationships between feldspar destruction and clay

production (Nesbitt and Young, 1982) as a way to understand the role chemical

weathering has on sediment composition (Nesbitt and Markovics, 1980; Roser and

Korsch, 1988; Nesbitt and Young, 1996; Young and Nesbitt, 1998). As the understanding

of the types of compositional changes that occur during soil formation improved, major-

element compositions of sediments were used to interpret source rock compositions

(Roser and Korsch, 1988; Fedo et al., 1995).

2

Groundbreaking geochemical work by Taylor and McLennan (1985) used trace-

element patterns from sedimentary rocks to determine the average composition of the

upper continental crust and its evolution, which subsequently broadened the application

of using trace elements and rare-earth elements (REE) for provenance interpretation. Key

findings presented in Taylor and McLennan (1985) suggested that certain trace elements

with low solubility values (e.g. Zr, Hf, Sc, Cr, Th, Co and the REEs), and thus low

residence times in water, are quantitatively transferred to the sedimentary record from

source, regardless of denundational processes. Under this principle, many studies have

expressed trace element compositions of sediment and sedimentary rocks as derived

ratios (e.g. Th/Sc, La/Sc, Cr/Th, Th/Co) to interpret sources with similar geochemical

characteristics (e.g. Bhatia and Crook, 1986; Wronkiewicz and Condie, 1987; McLennan,

1989; Feng and Kerrich, 1990; McLennan and Taylor, 1991; Condie et al., 1992;

McLennan et al., 1993; Cullers, 1994; Fedo et al., 1996; Fralick and Kronberg, 1997;

Holail and Moghazi, 1998; Armstrong-Altrin et al., 2004; Cullers, 2002; Oni et al., 2014;

Eizenhöfer et al., 2015; Xiang et al., 2015).

Caution must be taken when using provenance discriminating techniques whose

basis is the transfer of major or trace elements to the sedimentary record via chemical

weathering, because such approaches disregard the notion that sediment may partly

acquire its composition by mechanical processes during transport. In particular, mineral

fractionation (i.e., sorting) causes concern in evaluating provenance (Cullers et al., 1987;

Cullers, 1988; Nesbitt and Young, 1996; Fedo et al., 2015) because sorting is governed

by how different minerals behave in water flow based upon their textural properties (e.g.

density, shape, and crystal structure) that commonly result in the preferential

3

concentration of certain minerals into different grain-size fractions. This means that

sorting introduces the possibility that some sediment fractions will become enriched in

accessory minerals abundant in specific trace elements. Because trace elements and the

minerals that they are incorporated in are linked to each other, elemental ratios commonly

used to infer source composition may reveal geochemical values that are disproportionate

to those of the actual provenance if minerals holding trace elements have become either

concentrated or depleted in a fraction of sediment. As a result, it should be expected that

some elemental ratios used for revealing source compositions may be impacted by

sorting.

Despite the effects that sorting could impose on the composition of sediment,

source-discriminating ratios are still extensively used to interpret provenance under the

assumption that the chosen elements behave as a closed system during weathering and

are quantitatively transferred to the sedimentary record. Recent studies (e.g. Singh, 2009;

Schoenborn et al., 2012; Tang et al., 2012) use either trace-element signatures, elemental

ratios, or REE patterns to infer the possible sources of sediment without accounting for

the possible effects of sorting. In light of this situation, and following on the approach in

Nesbitt and Young (1996) and Nesbitt et al. (1997), a controlled study is needed that aims

to understand how siliciclastic sediment directly receives its composition from a single,

simple geologic system with a known sediment source. Such a study can be conducted by

going to a location that eliminates, minimizes, or controls the intensity of all other

processes capable of modifying sediment composition.

Modi (2011) conducted such a study in the Stepladder Mountains in the Mojave

Desert, CA (Fig. 1). The work was designed to test whether a mineralogical and

4

Figure 1. Map of the field area in the Mojave Desert, southeastern CA. The watershed site lies in the

northern tip of the granitic Stepladder pluton (Ksp). Other exposed lithological units are marked. The red

line marks the path in which sediment samples were collected across the pediment dome by Modi (2011).

5

geochemical provenance reconstruction of first-cycle sediment produced in an arid

climate would correctly predict the source composition. That study area is located in a

geological setting where sediment should ideally reflect source composition because: (1)

the sediment in the vicinity is solely derived from the granodiorite Stepladder pluton

(Modi, 2011), (2) the effects of chemical alteration on the bedrock or sediment are

minimal because the region has been arid to semiarid since the early Holocene

(McDonald et al., 2003), and (3) the sediment is currently in active transport and,

therefore, has not yet been compositionally modified by diagenesis. Results from Modi

(2011) recognized considerable deviations in the provenance-indicating, trace-element

signatures from those of the bedrock. Modi (2011) interpreted the findings as a result of

mineral sorting across 8 km of transport. However, collected sediments were scattered

from the source to the lower plain of the piedmont (Fig. 1), prompting the concern that

extrabasinal components were delivered by wind. Rare-earth element (REE) signatures in

sediment derived from the pluton indicated that granitic bedrock from the Stepladder

pluton is more compositionally similar to coarser-grained sediment than finer-grained

sediment, although neither size group is the same as bedrock compositionally. Despite

that all sediment in the region was most likely derived from the granitic Stepladder

pluton, data scattered across a trace element plot commonly used for the assessment of

source mixing permitted up to 10% of an endmember basalt in the fine sediment

population (Modi, 2011).

Given the concern that wind-blown material might be a problem, and that the

sampling traverse ranged from a mountainous source to an alluvial plain, the findings of

Modi (2011) inspired an effort to further control the variables associated with source

6

mixing by refining the study area in Modi (2011) to a single, small watershed (Fig. 2A)

contained entirely within the mountainous source area of the Stepladder pluton. This

setting experiences high rates of downcutting (Dohrenwend, 1988) and therefore contains

recently formed and transported sediment. Shallow, narrow fluvial channels within the

watershed dissect the local bedrock and saprolite, and similar to the Modi (2011) study,

contain sediments that have been naturally sorted into different grain-size populations

that span from very fine sand to gravel (Fig. 3A-B). Given the results of Modi (2011),

this observation prompts the question: even after very minimal transport, can sorting

cause mineralogical components, and thus geochemical signatures in sediment, to deviate

significantly from those of the source rock before sediment leaves the source area? If the

preferentially sorted sediment is not geochemically equivalent to the source, then

transport of almost any length holds the capacity to impose changes in sediment

composition from source through the process of sorting. The purpose of this study is to

apply field work coupled with the utilization of petrographic and geochemical techniques

to examine whether the composition of sediments can be modified substantially enough

during very short transport distances (0-500 m from source), where geochemical

signatures fail to reconstruct provenance composition accurately.

7

Figure 2A-D. Oblique low altitude aerial image looking west into studied watershed in the Stepladder

Mountains, CA. (A) Boundary of watershed used in this study. Watershed margin is delineated in red. Two

main channels are marked in white, with smaller feeding channels in blue. Black box indicates location of

channel confluence where sediment samples were collected. (B) Topographic profile of the dotted white

cross section line from A to A’. (C) Topographic profile of the south channel. (D) Topographic profile of

north channel.

8

Figure 3A-B. Channel area holding sorted Stepladder sediments. (A) Direct overhead image of bending

channel. White arrow denotes the direction of sediment transport. (B) Outline of the channel field site with

general locations of grain-size populations. White arrow denotes the direction of sediment transport.

Coordinates for channel area: 34°40’18.5’’N, 114°50’22.3’’W.

9

2. GEOLOGIC SETTING

The oldest basement rocks documented in the local area of the Stepladder

Mountains consist of Paleoproterozoic gneisses and schists that underwent regional

metamorphism at 1.7 Ga during the Ivanpah orogeny (Dewitt et al., 1984; Thomas et al.,

1988; Wooden and Miller, 1990). These metamorphic rocks were later intruded by

granitoids (1.76 to 1.64 Ga; Wooden and Miller, 1990), potassium-rich granites (1.4 Ga;

Anderson and Bender, 1989), and diabase dikes (1.1 Ga; Miller and Wooden, 1994). By

the Neoproterozoic, a stable craton developed upon which kilometers of sedimentary

strata consisting of clastic and carbonate rocks were unconformably deposited (Fedo and

Cooper, 2001). Tectonic activity during the Late Cretaceous was associated with the

Laramide Orogeny and spurred regional magmatism and high-grade metamorphism

(Anderson and Cullers, 1990), which resulted in the emplacement of widespread granitic

plutons, including the Stepladder pluton, in the middle to upper crust (Miller and

Wooden, 1994). Crustal thinning during the late Miocene within the Colorado River

extensional corridor exposed rocks at the Earth’s surface from depths down to 15 km

(Howard and John, 1987), including the Stepladder pluton.

The Stepladder pluton is now exposed as a topographic dome (Fig. 1) with a low

sloping pediment that extends away from the highlands where all channels drain away

from the center of the range. Such landforms in the Mojave Desert, commonly referred to

as pediment domes, are desirable locations to study rates of sediment erosion,

transportation, and deposition. Cosmogenic nuclide models used to date the ages of

exposed grains on Mojave pediment domes have shown that nuclide activities increase

downslope (Nichols et al., 2002), which implies downwearing rates are the greatest in

10

mountainous areas with the steepest topography. Depositional rates of piedmont

sediments in the Mojave Desert increase between 18 to 39 mm/ky throughout the

Pleistocene (Nichols et al., 2005), until the early Holocene when the climate shifted to

arid conditions. Due to the low annual rainfall in the Mojave Desert (12 cm/year; Stoffer,

2004), sediments are transported only decimeters per year across piedmonts (Nichols et

al., 2002; Nichols et al., 2005). Greatest lengths of sediment transport occur within

channel systems, where sediments can be transported several meters per year (Nichols et

al., 2005) during strong rain events.

11

3. CHARACTERIZATION OF WATERSHED

The study area for this work is a small watershed (0.1 km2; Fig. 2A) located on

the east side of the central axis of a topographic dome at the northern tip of the

Stepladder Mountains, southeastern CA (Fig. 1). Maximum topographic relief in the

watershed is ~ 50 m, although this is based on the anomalously high peak at the southern

boundary of the watershed (Fig. 2A). Excluding the peak, the common relief from the

outer margin of the watershed to the lowest point at the southeastern margin is ~ 30 m.

Exposed bedrock in the watershed is fresh to slightly weathered, where the latter

forms a saprolite at the surface. Fresh bedrock and saprolite are best exposed in the study

area in the form of inselbergs and rocky outcrops. However, bedrock lies only

centimeters beneath the erosional surface throughout the entire watershed (Fig. 2A).

Two large stream channels dissect the exposed bedrock and saprolite in the

watershed and hold loose, unconsolidated sediment (Fig. 2A). Many lower-order streams

bring sediment from higher elevations to the two main channels that are separated by a

divide, that is topographically lower than the watershed boundary (Fig. 2B). The southern

channel has a relief of 20 m (Fig. 2C), whereas the northern channel has a stream relief of

17 m (Fig. 2D). The southern and northern channels are approximately 430 and 400 m

long in length before they reach a confluence at the southeastern margin of the watershed,

where samples used in this study were collected. Stream gradients are 46.5 and 37.5

m/km for the southern and northern channels, respectively.

The channel section (~ 5 m wide) at this confluence (Fig. 3A) contains sediment

sorted into multiple grain-size fractions (Fig. 3B) during fluvial transport. Sediments

toward the outer section of the channel section are fine enough to produce mud cracks

12

during desiccation. Local small patches of accessory mineral deposits that contain

distinctively darker grains are located in the main channels.

13

4. METHODS

4.1 Field Work

Five sediment samples (CD-1, CD-2, CD-3, CD-4, and CD-5; Fig. 4A-E) were

collected in the channel (Fig. 3B) at the confluence of the north and south channels.

Samples were collected with a shovel from areas where grain size was relatively

consistent at the surface and at depth (~30 cm) and placed into locking plastic bags.

Additional samples collected within the watershed include one magnetite concentrate

(CD-M; Fig. 4F), one fresh bedrock sample (CD-BR), and one saprolite sample (CD-

SAP). Structural measurements were made on joint surfaces of exposed bedrock across

the field area.

4.2 Textural Analysis and Sample Preparation

To determine the grain-size distributions of the samples, each was individually

sieved from -2 to 5 Φ in 0.5 Φ intervals (Table 1). Other statistical parameters of grain-

size distributions, such as mean, median, mode, kurtosis, skewness, and modality

following the approach in Folk and Ward (1957), were calculated (Table 1) by using the

particle size analysis software GRADISTAT (Blott and Pye, 2001). Following sieving,

each sample (CD-1, CD-2, CD-3, CD-4, and CD-5; Fig. 4A-E) was re-homogenized and

coned-and-quartered into two separate aliquots, one for thin section petrography and the

other for geochemical analysis.

In order to produce thin sections, sediment aliquots were stabilized in epoxy then

cut into rectangular billets. The saprolite thin section was cut out from a hand sample of

friable saprolite, bathed in epoxy, vacuum impregnated, dried, and cut into a rectangular

14

Figure 4A-F. Images of five samples collected from the channel section and the magnetite concentrate. (A)

CD-1 – very fine gravel; (B) CD-2 – very coarse sand; (C) CD-3 – medium sand; (D) CD-4 – fine sand; (E)

CD-5 – very fine sand. (F) Magnetite concentrate, CD-M, was collected as a heavy mineral deposit near the

channel section.

15

Table 1. Textural descriptions for Stepladder sediments

aTextural classifications and calculations after Folk (1974). dSorting calculated after Folk (1974). bRoundness calculated using rho scale from Folk (1955) and diagrams from Powers (1953). Scale: 0 (very angular) to 6

(very rounded). cGrain sizes represented in phi (Φ) units where Φ = -log2(d). d = grain size measured in mm. Abbreviations: vf = very

fine; f = fine; m = medium; vc = very coarse. eSkewness calculated from Folk (1974): Sk = (Φ 95- Φ5)/2.44(Φ 75- Φ 25). fKurtosis calculated from Folk (1974): K = (Φ16+Φ84-2Φ50) / 2(Φ16+Φ84) + (Φ5+Φ95-2Φ50) / 2(Φ95+Φ5).

Stepladder Sediments

CD-1 CD-2 CD-3 CD-4 CD-5 CD-M

Textural

Classa

Sandy gravel Sandy gravel Gravelly sand Gravelly sand Muddy sand Gravelly sand

Modality Bimodal Unimodal Unimodal Unimodal Unimodal Unimodal

Roundingb 1 1 1 2 2 1

Very angular Very angular Very angular Angular Angular Very angular

Avg. grain

sizec (x̄)

-1.245 Φ

vf Gravel

-0.726 Φ

vc Sand

1.008 Φ

m Sand

2.415 Φ

f Sand

3.621 Φ

vf Sand

1.72 Φ

m Sand

Sortingd (σ) 1.1 1.841 0.873 0.980 0.794 0.895

Poor Poor Moderate Moderate Moderate Moderate

Skewnesse

(Sk)

0.365

Very fine

skewed

0.632

Very fine

skewed

-0.038

Symmetrical

0.100

Symmetrical

-0.010

Symmetrical

-0.370

Very coarse

skewed

Kurtosisf (K) 1.035 0.871 1.128 1.130 0.954 1.30

Mesokurtic Platykurtic Leptokurtic Leptokurtic Mesokurtic Leptokurtic

Grain-size distributions in %

-2 Φ 31 38 0 0 0 0

-1.5 Φ 16 12 1 0 0 1

-1 Φ 16 9 1 0 0 1

-0.5 Φ 13 7 3 0 0 2

0 Φ 8 5 7 1 0 3

0.5 6 5 14 1 0 4

1 Φ 3 4 23 3 0 7

1.5 Φ 2 4 25 9 1 11

2 Φ 1 4 16 19 2 25

2.5 Φ 1 3 6 23 5 31

3 Φ 1 2 2 19 13 13

3.5 Φ 1 2 1 11 23 2

4 Φ 0 2 1 7 25 0

4.5 Φ 0 1 0 4 16 0

5 Φ 1 2 0 3 15 0

Total 100 100 100 100 100 100

Sieving Error 0.1 % 0.2% 0.0% 0.2% 0.1% 0.2%

16

billet. Two bedrock thin sections were made by cutting sample CD-BR into two

rectangular billets, referred to as CD-BR1 and CD-BR2. All billets were made into

conventional 25 x 46 mm polished thin sections.

Aliquots of sediment samples reserved for geochemical analysis were pulverized

in a ceramic shatterbox dish. Two aliquots of the coarsest sample (CD-1; Fig. 3A) were

powdered separately and treated as individual samples during geochemical analysis to

test for reproducibility in the dissolution process.

4.3 Petrography

Petrographic work was performed on thin sections using a Nikon LV100D POL

microscope with a Conwy Valley Systems automated point counter attached to a

computer. The program PETROG was used to create a grid of points for counting across

the thin section space. Modal compositions of each sample were determined by point

counting procedures using the Gazzi-Dickinson (Dickinson, 1970; Ingersoll et al., 1984)

approach, where the mineralogical composition at 500 to 600 points across each thin

section was identified (Table 2). For comparison with the Gazzi-Dickinson point

counting technique, the Folk approach (Folk, 1974) was also employed that involves

counting any polymineralic grains as lithic fragments regardless if the mineral under the

cross hair is identifiable. General observations of clast roundness and shape were

accomplished using a Nikon SMZ-800 incident light microscope (Table 1).

4.4 Geochemical analysis

Geochemical analyses were conducted by using powdered aliquots of the five

collected sediment samples and the magnetite concentrate. Major (Table 3) and trace-

element (Table 4) contents were determined by inductively coupled mass spectrometry

17

Table 2. Point-counted mineralogical modes of Stepladder sediments, saprolite, and bedrock.

Qm: total monocrystalline quartz

Qp: total polycrystalline quartz

P: total plagioclase

K: total K-feldspar;

total feldspar (P+ K)

B: total biotite

Cc: total calcite from caliche

D: total opaque minerals

Ap: total apatite

Zr: total zircon

L: total lithic fragments

Total: total points counted as minerals

Misc: unidentifiable grains

n: total points counte

Sediment Samples Bedrock Saprolite

CD-1 CD-2 CD-3 CD-4 CD-5 CD-BR1 CD-BR2 Avg. CD-SAP

Po

int

Co

un

tin

g R

esu

lts

Qm 97 116 105 95 72 136 210 173 69

Qp 10 5 1 3 0 13 2 7.5 41

P 99 123 125 125 84 208 210 209 229

K 108 126 81 79 52 108 41 74.5 122

B 9 17 36 55 89 17 28 22.5 19

Cc 2 1 12 5 5 0 0 0 0

Op 1 7 9 13 20 6 6 6 6

Ap 0 1 0 3 3 3 1 2 2

Zr 0 0 0 1 2 0 0 0 0

Total 326 396 369 379 327 491 498 495.5 490

Misc 2 6 4 44 129 0 0 0 0

Folk QFL

No

rma

lize

d m

iner

alo

gy

(%

)

Q 1 14 21 29 34 - - - -

F 4 27 52 59 63 - - - -

L 95 59 27 12 3 - - - -

Gazzi-Dickinson QFL

Q 35 33 34 32 35 - - - -

F 65 67 66 68 65 - - - -

L 0 0 0 0 0 - - - -

Q 34 33 34 32 35 32 46 39 24

P 32 33 40 42 40 45 45 45 50

K 34 34 26 26 25 23 9 16 26

Q 33 32 30 27 24 31 43 37 23

F 64 64 60 57 46 66 51 59 73

B 3 4 10 16 30 3 6 4 4

18

Table 3. Major element oxides for Stepladder sediment, bedrock, and saprolite. Oxides reported in weight percent.

SiO2 TiO2 Al2O3 Fe2O3 MnO MgO CaO Na2O K2O P2O5 CO2 LOI Total CIA

Sediment Samples

CD-1 (1) 74.95 0.2 13.07 1.24 0.02 0.26 1.32 3.23 4.87 0.06 0.09 0.89 100.1 50.8

CD-1 (2) 75.6 0.18 12.47 1.25 0.02 0.26 1.44 2.99 4.04 0.05 0.11 0.89 99.19 51.9

Avg CD-1 75.27 0.19 12.77 1.24 0.02 0.26 1.38 3.11 4.45 0.06 0.1 0.89 99.64 51.4

CD-2 71.9 0.34 13.02 2.16 0.03 0.5 2.01 3.54 3.87 0.1 0.19 1.35 98.89 50.1

CD-3 66.7 0.54 16.66 2.45 0.04 0.69 2.68 4.9 3.38 0.15 0.28 2.02 100.2 51.6

CD-4 59.81 0.59 17.25 3.46 0.06 1.19 4.12 4.62 2.83 0.22 1.04 4.62 98.77 53.1

CD-5 58.79 0.63 16.45 4.06 0.08 1.79 4.39 3.23 2.67 0.18 1.36 7.67 99.93 56.6

Magnetite Concentrate

CD-M 21.5 5.71 5.34 60.66 0.26 0.31 1.33 1.34 0.99 0.5 - 0.63 98.57 -

Bedrock*

ST09-02 70.71 0.33 15.38 1.93 0.03 0.57 2.09 4.76 3.63 0.11 - 0.85 100.39 50.1

CF00-18 71.84 0.31 15.09 1.68 0.03 0.61 2.27 4.66 3.45 0.10 - 0.65 100.69 49.7

CF96-4 71.39 0.25 15.32 1.75 0.03 0.48 2.01 4.24 4.19 0.10 - 0.44 100.2 50.7

CF96-8 73.69 0.22 14.75 1.45 0.03 0.49 1.92 4.4 3.37 0.08 - 0.51 100.91 51

Avg 71.91 0.28 15.14 1.70 0.03 0.54 2.07 4.52 3.66 0.10 - 0.61 - 50.4

Saprolite*

CF00-04 71.59 0.29 14.54 1.9 0.02 0.4 1.85 4.23 4.11 0.08 0.02 0.75 99.78 50

CF00-05 73.69 0.23 14.48 1.41 0.02 0.36 1.82 4.24 3.94 0.09 0.12 0.57 100.97 50.7

Avg 72.64 0.26 14.51 1.66 0.02 0.38 1.84 4.24 4.03 0.09 0.07 0.66 - 50.3

*Data from Modi (2011)

19

Table 4. Trace element analyses of Stepladder samples. Element abundances reported in ppm.

*Data from Modi (2011)

Sediment Samples Bedrock* Saprolite*

CD-1

(1)

CD-1

(2)

CD-1

Avg.

CD-2 CD-3 CD-4 CD-5 CD-M Avg. Avg.

Be 2 2 2 2 3 3 3 2 2.6 1.9

Sc 1.5 1.3 1.4 2.8 4 6.2 8.2 16.1 0.62 0.63

V 20 17 18.5 31 38 53 61 928 21.73 17.24

Cr - - - 13 - 32 23 130 1.51 1.33

Co 1 1 1 3 3 6 8 24 1.21 1.18

Cu 20 20 20 10 10 20 50 10 1.99 1.87

Zn 30 30 30 50 50 80 90 230 11.47 16.46

Ga 16 15 15.5 19 23 24 22 46 16.56 15.61

Ge 1.1 1 1.05 1.1 1.3 1.7 1.6 2.2 - -

Rb 103 94 98.5 108 103 95 95 29 44.56 63.74

Sr 423 390 406.5 431 494 496 421 165 345.3 296.97

Y 4.5 4.2 4.35 8.2 9.3 19.9 25.8 99.7 6.17 4.53

Zr 101 103 102 162 178 242 352 2381 170.2 130.75

Nb 2.50 1.90 2.20 5.50 9.30 8.70 10 58.20 7.42 5.67

Cs 0.60 0.60 0.60 1 1.20 1.70 2.50 0.40 0.97 0.65

Ba 1420 1137 1278.5 813 541 558 626 329 744.02 755.1

La 22.4 21.5 21.95 32.6 30.2 47.6 48.3 1160 21.74 20.39

Ce 42.3 40.7 41.5 63.8 60 95.7 94.9 2440 32.86 32.64

Pr 4.47 4.34 4.4 6.8 6.48 10.5 10.9 231 4.68 4.39

Nd 15.3 15.1 15.2 25 23.5 38.2 39.7 807 16.45 15.1

Sm 2.31 2.38 2.34 4 3.95 7.08 7.73 116 2.63 2.36

Eu 0.63 0.625 0.63 0.77 0.84 1.26 1.38 5.16 0.7 0.64

Gd 1.48 1.51 1.49 2.59 2.79 5.07 5.98 60.4 1.7 1.52

Tb 0.18 0.19 0.18 0.33 0.36 0.7 0.87 6.32 0.22 0.19

Dy 0.85 0.94 0.89 1.72 1.92 3.71 4.65 26.5 1.07 0.94

Ho 0.15 0.16 0.15 0.3 0.33 0.67 0.88 3.79 0.19 0.17

Er 0.45 0.45 0.45 0.84 0.91 1.78 2.46 9.03 0.5 0.44

Tm 0.06 0.06 0.06 0.12 0.13 0.27 0.36 1.07 0.07 0.06

Yb 0.45 0.42 0.43 0.74 0.85 1.78 2.43 6.19 0.46 0.4

Lu 0.07 0.06 0.07 0.1 0.11 0.26 0.38 0.94 0.07 0.06

Hf 2.2 2.1 2.15 4.1 4.6 5.1 5.9 59.3 4.72 3.65

Ta 0.4 0.29 0.34 0.51 0.8 1.06 1.05 5.18 0.47 0.38

Tl 0.37 0.35 0.36 0.42 0.47 0.22 0.31 0.14 0.43 0.42

Pb 10 10 10 12 14 24 24 46 10.33 13.71

Th 6.28 5.73 6 10.8 18.1 14.3 11.3 571 6.61 5.74

U 1.02 0.83 0.92 1.47 2.49 2.1 2.41 37.3 0.29 0.39

20

and instrumental neutron activation analysis (FUS-ICP/MS; INAA) through Activation

Laboratories Ltd. under the Lithogeochemistry Research Package. Detection limits of

most major oxides were at 0.01 wt. %, with the exception of Mn and Ti that had detection

limits of 0.001 wt. %. A total of 45 trace elements were analyzed in parts per million with

detection limits that varied per element.

Approximately 10 mg of each powdered sample was used to determine total

carbon and carbonate CO2 by coulometry with combustion and acid evolution techniques,

respectively. Results were corrected for carbonate and phosphate content by subtracting

CaO and P2O5 from total CaO to obtain the CaO contents in the silicate fraction only.

Precision for analytical uncertainty for coulometry was better than 1% for all samples.

21

5. ANALYSIS OF STEPLADDER BEDROCK AND SAPROLITE

In order to test for the compositional variability between bedrock and locally

derived sediment, it is essential to establish a single reference composition of fresh

bedrock to compare with the sediment. As both fresh bedrock and saprolite outcrops are

exposed throughout the watershed and contribute to sediment production, the petrology

and geochemistry of each were also compared to each other to ensure they are

compositionally similar. Original geochemical data for bedrock and saprolite come from

Modi (2011).

5.1 Stepladder Bedrock

5.1.1 Petrology

In the field, Stepladder bedrock was classified as a compositionally and texturally

homogenous, coarse-grained biotite granodiorite with a hypidiomorphic igneous fabric

(Fig. 5). The two bedrock thin sections examined (CD-BR1 and CD-BR2) are chiefly

composed of plagioclase, followed by quartz, K-feldspar, and biotite (Table 2). In Quartz

– Alkali feldspar – Plagioclase (QAP) compositional space (Streckeisen, 1976; Appendix.

Fig. D1), bedrock samples CD-BR1 and CD-BR2 are classified as granodiorite, as Modi

(2011) also found. Mineralogical variety between the two samples within the granodiorite

field can be attributed to how much area on the 25 x 46 mm thin section was accounted

for by a single K-feldspar megacryst (typically ranging from 1 – 3 cm; Fig. 5B).

Plagioclase is the most abundant mineral in the Stepladder granodiorite and

commonly occurs as euhedral to subhedral megacrysts with distinctive concentric zoning

and albite twinning (Fig. 5C). Clay alteration occurs in plagioclase predominately along

twinning planes or within calcic zones (Fig. 5C). Potassium feldspar occurs as either

22

Figure 5A-D. Bedrock field and hand sample photographs and photomicrographs. (A) Surface of fresh

Stepladder granodiorite (B) Hand sample of Stepladder granodiorite used for thin sectional analysis. Note

size of K-feldspar phenocryst. (C) Photomicrograph of bedrock (crossed polarized) showing slight clay

alteration of plagioclase grain. (D) Photomicrograph of bedrock (crossed polarized) showing albite

twinning of plagioclase and undulose extinction of quartz. Abbreviations: Plag = plagioclase; Ksp = K-

feldspar; Qtz = quartz; Bt = biotite.

23

subhedral to euhedral perthitic megacrysts or microcline with inclusions of quartz,

plagioclase, biotite, and accessory minerals (Fig. 5C). Quartz mostly occurs as subhedral

interstitial crystals that commonly exhibit undulatory extinction (Fig. 5D), but also occurs

as polycrystalline aggregates. Biotite, the dominant mafic mineral, occurs predominately

as elongated interstitial grains (Fig. 5D) or poikilitically included in plagioclase and K-

feldspar megacrysts. Minor chlorite replaces biotite crystals along grain boundaries and

cleavage planes (Fig. 5D). Accessory phases, such as apatite, zircon, and magnetite,

occur either as interstitial grains or as poikilitic inclusions.

5.1.2 Geochemistry

All geochemical data of the Stepladder pluton summarized here come from Modi

(2011), where four samples of bedrock were analyzed for major-, trace-, and rare-earth

element contents. For this study, the average geochemical composition of the four

Stepladder bedrock samples was calculated in order to have a single set of geochemical

data to compare with sediment (Tables 3-4).

5.1.2.1 Major Elements

Other than normalized mineralogy, numerous compositional variables and plots

can be used to characterize the bedrock. The SiO2 content of the Stepladder bedrock

ranges from 70.7 to 73.7 wt. % with an average of 71.9 % (Table 3). Ratio values of

A/CNK (Al2O3/CaO+Na2O+K2O; Shand, 1943) and A/NK (Al2O3/ Na2O+K2O; Shand,

1943) ranges from 0.97 to 1.03 and 1.30 to 1.35, respectively (Appendix Table D1). The

Aluminum Saturation Index (ASI = Al/Ca – 1.67P + Na + K; Shand, 1943) ranges from

1.48 to 1.54, with an average of 1.50 (Appendix Table D1). The Fe-number (Fe* =

FeOtot/ FeOtot + MgO; Miyashiro, 1970) across bedrock samples ranges from 0.71 to 0.76

24

with an average value of 0.74 (Appendix Table D1). Alkali-lime indices of the bedrock

(Na2O + K2O – CaO; Peacock, 1931) range from 5.84 to 6.42, with an average of 6.11

(Appendix Table D1). Bulk geochemical compositions across all bedrock samples show

little variation between each other and are classified as alkali-calcic (Fig. 6A), magnesian

(Fig. 6B), peraluminous (Fig. 6C), and alkali granites (Fig. 6D) on different

discrimination plots.

5.1.2.2 Trace- and rare-earth elements

When discussing trace-element compositions used in provenance research,

elements are commonly divided into the following categories based upon groups of

elements with similar geochemical properties: large ion lithophile elements (LILEs; Rb,

Ba, Cs, Sr), transition metals (V, Co, Cr), and high field strength elements (HFSEs; Sc,

Y, Th, U, Pb, Zr, Hf, Nb, Ti), and rare-earth elements. Trace-element patterns of two

bedrock samples normalized to average Upper Continental Crust (UCC; McLennan,

2001) show considerable depletions in Rb, Cs, and U, and are strongly depleted in the

transition metals Co, Cr, and Sc (Fig. 7A).

Chondrite-normalized patterns of REEs are conventionally used in provenance

work describe the behavior of the LREEs (La, Ce, Pr, Nd, and Sm), HREEs (Gd, Tb, Dy,

Ho, Er, Tm, Yb, and Lu), total REE content, and Eu anomaly. Chondrite-normalized REE

contents of average Stepladder bedrock generate sub-parallel patterns with little

compositional variation between each sample (Fig. 7B). Chondrite-normalized ratios

between end-member LREEs, lanthanum and samarium (LaCN/SmCN = 5.16), indicate

that the LREEs are more fractionated than the HREEs (GdCN/YbCN = 2.98), with an

overall fractionation of (LaCN/YbCN) of 32.1.

25

Figure 6A-D. Geochemical plots characterizing Stepladder bedrock and saprolite samples. (A) Na2O +

K2O –CaO (Alkali-lime index) vs SiO2 (wt. %) of Frost et al. (2011). (B) FeOt/(MgO+FeOt) vs SiO2 (wt.

%) plot of Miyashiro (1974). (C) A/NK vs A/CNK plot of Shand (1943). (D) Na2O + K2O vs SiO2 bedrock

classification plot of Cox et al. (1979), where samples plot in the alkali-granite space. All plots use

geochemical bedrock data collected by Modi (2011).

26

Figure 7A-B. Bedrock and saprolite trace and rare-earth element spider-plots. All geochemical bedrock

and saprolite geochemical data from Modi (2011). (A) Bedrock samples and average saprolite trace

element contents normalized to Upper Continental Crust (McLennan, 2001). (B) All bedrock samples and

average saprolite REE contents normalized to chondrite (McDonough and Sun, 1995).

27

Europium anomalies are calculated by the geometric average of the ratio of

neighboring rare-earth elements Sm and Gd, assuming that the ratio between the

neighboring element concentrations remains constant (Eu*CN = (SmCN – GdCN)1/2;

McLennan, 1989). Ratios with values < 1 are considered negative anomalies, whereas

ratios > 1 are considered positive anomalies. Average Stepladder bedrock has a negligible

Eu anomaly (0.99; Table 5).

Cerium anomalies are calculated by the differences in concentration between

neighboring elements Pr and Nd, assuming that the difference in the neighboring

elements is constant (Ce*CN = 2 * PrCN – NdCN; Lawrence and Kamber, 2006). Average

Stepladder bedrock has a slightly negative chondrite-normalized Ce anomaly (0.83; Table

5).

5.2 Stepladder Saprolite

Saprolite is fractured at all scales throughout the watershed and is easily

decomposed into sand (Fig. 8A). In contrast to fresh bedrock, saprolite had a brown

varnish and a friable texture (Fig. 8B). The following section demonstrates that the

saprolite resembles fresh bedrock in terms of both petrology and geochemistry.

5.2.1 Petrology

Despite being fractured, Stepladder saprolite is mineralogically similar to fresh

bedrock. In QAP ternary space (Streckeisen, 1976; Appendix Fig. D1), the saprolite

sample CD-SAP plots within the granodiorite compositional field with comparable K-

feldspar contents observed in the bedrock sample CD-1. The saprolite sample is

composed of primarily plagioclase (46%), followed by quartz (22%), orthoclase (25%),

and biotite (4%) (Table 2). Observed accessory minerals include magnetite, apatite, and

28

Table 5. Chondrite- and bedrock-normalized rare-earth element ratios of Stepladder sediment, bedrock, and saprolite samples.

*Data from Modi (2011)

Sediment Samples Bedrock* Saprolite*

CD-1 Avg. CD-2 CD-3 CD-4 CD-5 CD-M Avg. Avg.

Bed

rock

No

rma

lize

d

Eu/Eu*BN 1.02 0.72 0.77 0.64 0.61 0.19 1.00 1.02

Ce/Ce*BN 1.31 1.40 1.36 1.34 1.29 1.49 1.00 1.04

LaBN/YbBN 1.07 0.93 0.75 0.57 0.42 3.96 1.00 1.08

GdBN/YbBN 0.93 0.95 0.89 0.77 0.67 2.64 1.00 1.03

LaBN/SmBN 1.13 0.99 0.92 0.81 0.76 1.21 1.00 1.05

Ch

on

dri

te

No

rma

lize

d

Eu/Eu*CN 1.03 0.73 0.77 0.64 0.62 0.19 1.01 1.03

Ce/Ce*CN 1.09 1.13 1.10 1.09 1.04 1.24 0.83 0.86

LaCN/YbCN 34.27 29.93 24.13 18.17 13.50 127.30 32.11 34.63

GdCN/YbCN 2.78 2.83 2.66 2.30 1.99 7.89 2.99 3.07

LaCN/SmCN 5.85 5.09 4.77 4.19 3.90 6.24 5.16 5.39

∑REE 89.77 139.71 132.38 214.58 220.92 4873.40 83.34 79.30

LREE Tot 87.52 135.56 127.77 205.41 208.89 4819.56 80.76 77.04

HREE Tot 2.25 4.15 4.61 9.17 12.03 53.84 2.58 2.26

LREE/HREE 38.84 32.62 27.68 22.39 17.36 89.51 31.30 34.09

29

Figure 8A-D. Saprolite field and hand sample photographs and photomicrographs. (A) Weathered field

saprolite. Note sediment directly below saprolite. (B) Hand sample of saprolite. Note friable texture. (C)

Photomicrograph of saprolite sample under cross polarized light showing condition of mineral surfaces. (D)

Photomicrograph of saprolite sample under cross polarized light showing fracture dissecting biotite and K-

feldspar. Abbreviations: Plag = plagioclase; Ksp = K-feldspar; Qtz = quartz; Bt = biotite.

30

zircon. Similar to bedrock, both plagioclase and K-feldspar grains appear slightly cloudy

from minor weathering, whereas quartz grains remained largely intact (Fig. 8C).

Fractures in the saprolite dissect grains regardless of mineralogical composition

and commonly follow cleavage planes of plagioclase, biotite, and K-feldspar (Fig. 8D),

while dissecting grains of K-feldspar and quartz. Large fractures commonly have a thin

coat of brown, autochthonous material as well as accumulations of small lithic fragments.

5.2.2 Geochemistry

Saprolite geochemistry is derived from Modi (2011), where two samples were

analyzed for major- and trace-element compositions. For this study, the average

geochemical composition of the two samples were calculated in order to have a single set

of geochemical content to compare with fresh bedrock and sediment (Tables 3-4).

5.2.2.1 Major elements

The SiO2 contents of the saprolite range from 71.6 to 73.7 wt. %, with an average

of 72.6 wt. % (Table 3). Ratio values of A/CNK and A/NK range from 1.43 to 1.45 and

1.74 to 1.77, respectively (Appendix Table D1). The ASI value range from 1.45 to 1.47

(Appendix Table D1). The Fe* values across saprolite samples range from 0.80 to 0.81

(Appendix Table D1). Alkali-lime indexes of the saprolite range from 6.36 to 6.49

(Appendix Table D1). Bulk geochemical compositions of all saprolite samples show little

variation between each other, and are classified as alkalic to alkali-calcic (Fig. 6A),

slightly ferroan to magnesian (Fig. 6B), peraluminous (Fig. 6C), and alkali granites (Fig.

6D) on different discrimination plots.

31

5.2.2.2 Trace- and rare-earth elements

The UCC-normalized trace-element pattern of average saprolite closely followed

the composition of average bedrock that displayed considerable depletions in Rb, Cs, and

U and was heavily depleted in Co, Cr, and Sc (Fig. 7A). Average saprolite chondrite-

normalized REE contents possessed a pattern similar to average bedrock with steeply

fractionated LREEs (LaCN/SmCN = 5.39; Table 5) relative to HREEs (GdCN/YbCN = 3.07;

Table 5) (Fig. 7B). Average saprolite had a slightly negative Ce anomaly (0.86; Table 5)

and a negligible Eu anomaly (1.03; Table 5).

5.3 Joint Sets

Exposed outcrops of granodioritic bedrock are crosscut by three distinct joint sets,

which were observed in outcrops throughout the watershed (Fig. 9). Fracture spacing

varied from meter scale (Fig. 9B) to millimeter scale (Fig. 9C). A total of 57 strike-and-

dip measurements were taken across the watershed (Fig. 9D; Appendix Table B1) and the

orientations plotted on a lower hemisphere equal-area stereonet (Fig. 9E). Out of the

three joint sets, the dominant fracture system strikes NE, with a steep vertical-to-SE dip

(Fig. 9E). In lesser prevalence, but still readily seen was the NW striking joint set with a

steep vertical-to-NE dip (Fig. 9E). The least common joint set strikes NE, with a shallow

westward dip (Fig. 9E).

32

Figure 9A-E. Fracture system field photographs and joint orientations. (A) Field photograph of exposed

bedrock in watershed, showing joint sets 1 and 3 (2 not visible from camera angle). (B) Outcrop showing

meter scale fractures. (C) Outcrop showing microscale fractures and sediment production. (D) Aerial view

of watershed showing location of 50 strike/dip measurements taken in field (white dots). Multiple

measurements were taken at some locations. Outline of watershed is delineated in white. (E) Stereonet

projection of 57 total measured joints across watershed. Bold projections indicate the average of each joint

set.

33

6. ANALYSIS OF STEPLADDER SEDIMENT

6.1 Textural analysis

All sediment samples were sieved to determine grain-size distribution of each

sample. Each sample has an average mean grain size that falls into a unique Φ bin (Fig.

10) based upon the Wentworth grain-size classification scale (Wentworth, 1922). The

collective average grain-size distributions of all sediment samples range from very fine

gravel to very fine sand (x̄ = -1.2 Φ to 3.6 Φ; Table 1). Standard deviation values for each

curve do not deviate considerably between samples (σ = 0.7 to 1.8; Table 1). Skewness

values of curve shapes between samples range between 0.3 and -0.03 (very fine skewed

to symmetrical; Table 1). Kurtosis values range from 1.1 and 0.8 (Table 1).

6.1.1 CD-1

Sediment sample CD-1 is a very fine gravel with a mean grain size of -1.245 Φ

(Table 1; Fig. 10), across a range from fine gravel to very coarse silt, with the most

abundant clast size being very fine gravel. The sample is a poorly sorted (σ = 1.123),

bimodal, sandy gravel, with a fine skewed (Sk = 0.365), mesokurtic (K = 1.035) grain-

size distribution. In terms of grain shape, lithic fragments and monomineralic grains of

quartz, plagioclase, and K-feldspar are compact-bladed to compact-elongate, while biotite

is platy (Fig. 11A). On average, all grains are angular to sub-angular.

6.1.2 CD-2

Sediment sample CD-2 is a very coarse sand with a mean grain size of -0.726 Φ

(Table 1; Fig. 10), across a range from fine gravel to very coarse silt, which is similar to

CD-1 with very fine gravel being the most abundant clast size. The sample is a poorly

34

Figure 10. Frequency and cumulative percent distribution curves of the five sediment samples collected

across the channel section. Classifications for phi scale from -2 to 5 based on Wentworth scale (Wentworth,

1922).

35

Figure 11A-E. Channel sediment sample photomicrographs. (A) CD-1 – very fine gravel; (B) CD-2 – very

coarse sand; (C) CD-3 – medium sand; (D) CD-4 – fine sand; (E) CD-5 – very fine sand. All

photomicrographs are in plane polarized light.

36

sorted (σ = 1.841), unimodal, sandy gravel, with a fine skewed (Sk = 0.632), platykurtic

(K = 0.871), grain-size distribution. In terms of grain shape, lithic fragments and

monomineralic quartz, plagioclase, and K-feldspar grains are compact-bladed to

compact-elongate, while biotite is platy (Fig. 11B). On average, most grains are angular.

6.1.3 CD-3

Sediment sample CD-3 is a medium sand with a mean grain size of 1.008 Φ

(Table 1; Fig. 10), across a range from gravel to very coarse silt. The sample is a

moderately sorted (σ = 0.873), unimodal, slightly gravelly sand, with a symmetrical (Sk =

-0.038), leptokurtic (K = 1.128) grain-size distribution. In terms of grain shape, lithic

fragments and monomineralic quartz, plagioclase, and K-feldspar grains are compact-

bladed, while biotite is platy (Fig. 11C). On average, most grains are sub-angular, while

others are angular.

6.1.4 CD-4

Sediment sample CD-4 is a fine sand with a mean grain size of 2.415 Φ (Table 1;

Fig. 10), across a range from fine gravel to very coarse silt. The sample is a moderately

sorted (σ = 0.980), unimodal, slightly gravelly sand, with a symmetrical (Sk = 0.100),

leptokurtic (K = 1.130) grain-size distribution. In terms of grain shape, lithic fragments

and monomineralic quartz, plagioclase, and K-feldspar grains are compact-bladed to

compact-elongate, while biotite is platy to bladed (Fig. 11D). On average, most grains are

sub-angular, while others are angular.

6.1.5 CD-5

Sediment sample CD-5 is a very fine sand with a mean grain size of 3.621 Φ

(Table 1; Fig. 10), across a range from coarse sand to very coarse silt. The sample is a

37

moderately sorted (σ = 0.794), unimodal, muddy sand, with a symmetrical (Sk = -0.010),

mesokurtic (K = 0.954) grain-size distribution. In terms of grain shape, lithic fragments

and monomineralic quartz, plagioclase, and K-feldspar grains are compact-bladed, while

biotite is platy (Fig. 11E). On average, most grains are sub-angular, while few are

angular.

6.1.6 CD-M

The magnetite concentrate was collected from near the vicinity of the other

samples, but in a different channel. Sediment sample CD-M is a medium sand with a

mean grain size of 1.729 Φ (Appendix. Table C2), across a range from fine gravel to very

coarse silt. The sample is classified as a moderately sorted (σ = 0.895), unimodal, slightly

gravelly sand, with a very coarse skewed (Sk = -0.370), leptokurtic (K = 1.305) grain-size

distribution. The sample is largely composed of sub-angular, compact magnetite grains,

with some interspersed quartz, feldspar, and biotite.

6.2 Petrography

The mineralogical components of the sediment samples include plagioclase,

quartz, K-feldspar, biotite, magnetite, apatite, and zircon. Although the descriptive

characteristics of individual minerals (i.e., cloudy surfaces, twinning, chemical zoning,

crystal shape, etc.) remain the same between samples, average modal abundances of these

minerals vary across samples (Table 2). In particular, there is a systematic depletion of

quartz and K-feldspar and an enrichment of plagioclase (Fig. 12A) and biotite (Fig. 12B)

from fine to coarse samples.

All counted lithic fragments in sediment samples are amalgamations of the same

mineralogical components as found in the Stepladder bedrock. Using the Gazzi-

38

Figure 12A-D. QPK, QFB, and QFL plots of Stepladder sediments. Q = total quartz; F = total plagioclase

+ K-feldspar; L = total lithic fragments; B = total biotite; P = total plagioclase; K = K-feldspar. (A) QFL

rock classification ternary diagram based upon the Gazzi-Dickinson point counting method (Dickinson,

1970; Ingersoll et al., 1984). (B) QFL rock classification ternary diagram based upon the Folk point

counting method (Folk, 1974). Abbreviations: QA = quartz arenite; SA = subarkose; and SL = sublithic

arenite. (C) QPK ternary plot of Stepladder sediments, bedrock, and saprolite. (D) QFB ternary plot of

Stepladder sediments, bedrock, and saprolite.

39

Dickinson point-counting approach, all sediment samples plot as arkoses in Quartz –

Feldspar – Lithic (QFL) space (Fig. 12C). Using the Folk (1974) point-counting

approach, sediments plot across litharenite, feldspathic litharenite, lithic arkose, and

arkose classifications in QFL space (Fig. 12D). Abundances of lithic fragments

systematically decrease from coarser to fine-grained samples (Fig. 12D).

Caliche coats bedrock and fill fractures in saprolite in the Stepladder vicinity

(Modi, 2011), and occurs as clasts in the sediment samples. Caliche grains proportionally

account for less than 1% of all thin section mineralogy, except for sample CD-3 in which

it accounts for 3% of the sample (Table 2).

6.2.1 Quartz

In all samples, quartz occurs as sub-angular to sub-rounded, monocrystalline

grains or less commonly as polycrystalline aggregates (Fig. 11A-C). Both straight and

undulose extinction is present. As quartz is resistant to alteration, no clay minerals were

observed on grains. Quartz is abundant in all collected sediment samples and has a modal

abundance that ranges between 32 to 15%. Both monomineralic quartz and quartz

incorporated into lithic fragments was found to be more prevalent in coarser-sized

samples (CD-1 and CD-2).

6.2.2 Plagioclase

Plagioclase occurs as angular to sub-angular grains. Well-defined albite twinning

and oscillatory zoning are distinctive features in nearly all plagioclase grains, which both

locally occur in a single grain. As expected (e.g. Nesbitt and Markovics, 1997), the

occurrence of minor chemical weathering is more evident in plagioclase than any other

mineral in Stepladder sediment, as secondary clays gave grains a cloudy appearance

40

along twinning planes and the more calcic oscillatory zones. Plagioclase is abundant in

all sediment samples, and has a modal abundance that ranges between 18 to 33%.

Monomineralic plagioclase grains are particularly prevalent in the finer samples (CD-3,

CD-4, and CD-5), whereas lithic fragments containing plagioclase are more common in

coarser samples (CD-1 and CD-2). Using the Michel Levy method for determining

plagioclase composition, all measured grains across all samples are classified as

oligoclase (An22 and An30).

6.2.3 K-feldspar

Potassium feldspar in sediment most commonly occurs as perthitic megacrysts,

which locally display a slightly cloudy appearance, and suggests that clays have replaced

the exsolved plagioclase zones during hydrolysis. In addition to perthite, microcline

occurs as angular grains that locally exhibit minor alteration. Both perthite and

microcline contain poikilitically included grains of plagioclase, quartz, and accessory

minerals. Potassium feldspar increases in modal abundance from fine to coarser sediment

samples, and ranges from 11 to 33% (Table 2), respectively. Potassium feldspar grains, as

both monomineralic and within lithic fragments, are more prevalent in the coarser

sediment samples (CD-1 and CD-2).

6.2.4 Biotite

Biotite grains commonly have a platy shape with frayed edges. Alteration affects

many biotite grains through partial replacement by chlorite and Fe-oxides. Biotite

increases in modal abundance from coarser to finer grained samples with a range between

3 to 19%. Most commonly, biotite occurs as an monomineralic grain across all samples,

except for CD-1, in which it was mostly incorporated in a lithic fragment.

41

6.2.5 Accessory phases

As with the bedrock, magnetite, apatite, and zircon comprise the dominant

accessory phases within the sediment samples. In coarser samples (CD-1, CD-2, and CD-

3), accessory phases occur mostly as inclusions in biotite and plagioclase, whereas in

finer grained samples (CD-4 and CD-5), magnetite and apatite commonly occur as

monomineralic grains. All accessory phases increased in abundance from coarser to finer-

grained samples (Table 2).

6.3 Geochemistry

6.3.1 Major elements

There is a decrease in SiO2 content with decreasing grain size, ranging from 75.2

to 58.8 % from coarser to finer-grained samples (Table 3). Contents of K2O also decrease

with decreasing grain size. An opposite relationship is exhibited by the contents of TiO2,

Fe2O3, MgO, CaO, Na2O, and P2O5, all of which are systematically enriched with

decreasing grain size (Table 3). Coarser samples CD-1 and CD-2 are considerably

depleted in Al2O3 relative to finer-grained samples CD-3, CD-4, and CD-5 (Table 3).

6.3.2 Trace-elements

Trace-element contents of all sediment samples were normalized to the average

bedrock composition to illustrate differences in sediment composition relative to the

known source (Fig. 13A). Elements K, Ba, Sr, Hf, and Nb do not appreciably depart from

bedrock composition (less than 5x the average bedrock composition), whereas elements

Rb, Cs, Mn, Th, Pb, and Zr are highly variable between sediment samples (Fig. 13A).

The greatest departures from average bedrock composition are exhibited by elements Co,

Cr, Sc, Y, and U (Fig. 12A) for all samples. As expected for an accessory mineral

42

concentrate, sample CD-M is enriched with most trace elements, in particular V, Cr, Co,

Zr, and the REEs (Table 4).

Samples CD-1 and CD-3 have Cr values below detection limits (< 5 ppm). Values

of other elements mineralogically associated with Cr (i.e. Sc, Co, Fe) increase in

abundance from coarse to fine-grained samples (Appendix. Fig. D2), suggesting that an

analytical anomaly may have caused sample CD-3 to report Cr values below detection

limits; by contrast, the actual abundance of Cr in CD-1 is most likely below 5 ppm

because bedrock values are < 5 ppm. To determine what the Cr abundances of these two

samples may actually be, elemental abundances of Cr in two samples collected by Modi

(2011) with similar grain-size distribution curve shapes to CD-1 and CD-3 (Appendix.

Fig. C1) were used in an iterative analysis (Appendix. Fig. D3). Here, the Cr abundances

of the samples from Modi (2011) were used in conjunction with the Th and Sc

abundances collected in this study to be plotted in Cr/Th vs Th/Sc compositional space

against values of Cr ranging from 1 to 5. It is clear from this approach that Cr values for

CD-1 are actually below detection limits, whereas the low Cr value for CD-3 is most

likely an analytical error. Thus, the Cr values from the respective samples from Modi

(2011) will be used as proxy abundances for Cr values for samples CD-1 and CD-3 in

spider-plots and discrimination diagrams.

6.3.3 Rare-earth elements

In general, the total REE content of each sediment sample increases with

decreasing grain size (∑REE = 89.77 to 220.92 ppm; Table 5), as well as total LREE

(LREEtot = 87.52 to 208.89 ppm; Table 5) and HREEs (HREEtot = 2.25 to 12.03 ppm;

Table 5), which is typical in sedimentary deposits. Values of LREE/HREE decreased

43

with decreasing grain size (LREE/HREE = 38.84 to 17.36; Table 5), which confirms that

finer sediments are enriched with HREEs relative to LREEs.

Although the REE pattern of sample CD-1 most closely resembles the

composition of average bedrock (Fig. 13B), fine-grained samples progressively deviate

from bedrock composition. Chondrite-normalized REE contents of sediments generate

patterns with compositional variations between each sample (Fig. 13C). Chondrite-

normalized ratios indicate that the LREEs (LaCN/SmCN = 5.85 to 3.90; Table 5) are

overall more fractionated than the HREEs (GdCN/YbCN = 2.83 to 1.99; Table 5). Negative

Eu anomalies occur in nearly all sediment samples (the exception being sample CD-1;

Fig. 13B), where Eu/Eu*CN values became increasingly more negative with decreasing

grain size (Eu/Eu*CN = 1.03 to 0.62; Table 5).

Sample CD-M is strongly enriched in all REEs (∑REE = 4873.40 ppm, LREEtot =

4819.56 ppm, HREEtot = 53.84 ppm; Table 5) and like the channel sediments, exhibits

highly fractionated LREEs (LaCN/SmCN = 6.24; Table 5). However, CD-M exhibits a

much steeper slope for HREEs (GdCN/YbCN = 7.89; Table 5) than any other sediments.

The europium anomaly in sample CD-M is much more negative than any of the other

samples (Eu/Eu*CN = 0.19; Table 5).

Positive Ce anomalies occur in all sediment samples with Ce/Ce*BN, ranging from

1.29 to 1.49 (Table 5). Positive Ce anomalies have been interpreted to be the result of

weathering as Ce3+ oxidizes to insoluble Ce4+ (Braun and Pagel, 1994). In the case of

Stepladder sediments, a positive Ce anomaly is seen across all grain-size populations,

which does not considerably change between samples (Fig. 13B). This suggests the Ce

anomaly is likely a result of redox processes occurring during weathering.

44

Figure 13A-C. Trace- and rare-earth element plots for Stepladder sediments, saprolite, and bedrock. (A)

Trace element contents of sediments, and average saprolite normalized to average Stepladder bedrock. Red

square denotes value for Cr derived from Modi (2011) used for CD-1. Green triangle denotes value for Cr

derived from Modi (2011) used for CD-3. (B) REE contents of sediments and average saprolite normalized

to average Stepladder bedrock. (C) REE contents of sediments, magnetite concentrate CD-M, average

saprolite, and average bedrock normalized to chondrite (McDonough and Sun, 1995).

45

7. EVALUATION OF THE PROCESSES AFFECTING SEDIMENT

GEOCHEMISTRY

7.1 Chemical Weathering

The present climate of the Mojave Desert is arid (Stoffer, 2004). Consequently, it

is unlikely that compositional and geochemical variations in the modern channel

sediments were produced from extensive chemical weathering of Stepladder pluton

bedrock. However, to isolate mechanical sorting as the sole cause of compositional

variability amongst the collected samples, an examination of the extent of chemical

alteration in the studied sediments is needed.

The Al2O3–CaO*+Na2O–K2O (A–CN–K) compositional ternary diagram (Fig.

14A; Nesbitt and Young, 1984, 1989; Fedo et al., 1995) has been widely used to evaluate

chemical weathering trends. Early stages of chemical weathering begin with the

hydrolysis of plagioclase that results in the production of kaolinite, which plots directly

on the A apex (Fig. 14A). Thus, samples that endured chemical weathering should have

larger proportions of aluminous weathering products and follow a predictable trend

towards the A-apex parallel to the A-CN boundary (Nesbitt and Young 1984, 1989; Fig.

14A).

The Chemical Index of Alteration (CIA) is a numerical value between 50 and 100

used as an intensity scale for chemical weathering (Nesbitt and Young, 1982) and is

calculated as follows:

CIA = (Al2O3 / Al2O3 + CaO* + Na2O + K2O) * 100 (Eq. 1)

where the oxide values are in molecular proportions, and CaO* is representative of CaO

content in silicates only by subtracting apatite and carbonate components

46

Figure 14A-B. A-CN-K and A-CNK-FM compositional plots for the average Stepladder bedrock,

saprolite, and channel sediments. (A) A-CN-K compositional diagram. Note the fining of sediments toward

plagioclase composition. (B) A-CNK-FM compositional diagram. Note the fining of sediments toward the

FM apex. Both diagrams from Nesbitt and Young (1984, 1989).

47

(CaO* = CaOtot– (10/3)P2O5 – CO2; Nesbitt and Young, 1982, 1989). The CIA values of

individual samples represent the A values in A–CN–K space (Fig. 14A). Fresh granitic

bedrock and unweathered samples have CIA values of 50, whereas values greater than 80

indicate intense weathering (Fedo et al., 1995).

The four fresh Stepladder bedrock samples have an average CIA value of 50.3

(Table 3), indicating that bedrock has experienced negligible chemical weathering.

Similarly, the CIA value of saprolite is also 50.3 (Table 3), demonstrating a lack of

geochemical evidence for the chemical weathering of the saprolite. Thus, two possible

weathering histories are envisioned for the origin of the saprolite: (1) it formed under

wetter climatic conditions prior to the last glacial maximum and is a remnant of the

incipient zone of a weathering profile, or (2) it formed in equilibrium with the modern,

arid climate of the Mojave Desert. Regardless of either possibility, the saprolite releases

modern sediment identical in mineralogical composition to the fresh bedrock.

All sediment samples group along the feldspar join (Fig. 14A), and have CIA

values ranging from 50.1 to 56.6 (Table 3). These values indicate that chemical

weathering has had some, but overall a very minor effect on sediment composition.

Sample CD-5 had the highest CIA value, most likely because any small amount of

weathering products being produced from very minor plagioclase dissolution is

concentrated in finer grain-size populations during transport. Similar to the A–CN–K

diagram is the Al2O3–CaO*+Na2O+K2O–FeO+MgO (A–CNK–FM) diagram (Nesbitt and

Young, 1989; Fig. 14B), which includes Fe and Mg content. All sediments plot as a

group on the feldspar-FM tie line, which implies that no chemical weathering has

occurred to the sediment.

48

7.2 Physical Sorting

There is evidence to suggest that the compositional heterogeneity among samples

plotting along the feldspar tie line (Fig. 14A) is controlled by physical sorting. Samples

with larger average mean grain sizes (CD-1 and CD-2) plot to the right of average

bedrock and contain larger proportions of K-feldspar, whereas samples with smaller

average mean grain sizes (CD-3, CD-4, and CD-5) plot left of average bedrock and

contain larger proportions of plagioclase, which is similar to findings in Modi (2011). In

A–CNK–FM space (Fig. 14B), samples (CD-4 and CD-5) plot preferentially towards the

FM apex, which suggests that biotite and magnetite have become depleted in coarser

samples and are enriched in fine grained samples. These observations are supported by

point-counting data (Table 2), that demonstrate preferential concentration of biotite and

magnetite in fine-grained samples.

An explanation for this can be attributed to the differences in textural properties

of minerals in the Stepladder bedrock. The hydrodynamic shape of biotite allows it to

float in water during transport which increases the likelihood of biotite being sorted apart

from quartz and feldpsar during fluvial transport. Magnetite, conversely, has a greater

density (~5.15 g/cm3) than other minerals in the Stepladder bedrock (quartz ~ 2.65 g/cm3;

plagioclase ~ 2.68 g/cm3; and K-feldspar ~ 2.56 g/cm3), thus allowing it to become

preferentially sorted and concentrated. Considering that biotite and magnetite are both

minerals that possibly contain greater proportions of compatible trace elements than

quartz or feldspars, it is possible that physical sorting has distorted the immobile element

provenance signatures from source composition.

49

8. EVALUATION OF THE UTILITY OF PROVENANCE

INDICATORS

The overarching purpose of this research was to evaluate whether first-cycle

sediment that has travelled no further than a few hundred meters from its bedrock source,

that experienced no quantifiable chemical weathering, can predict the provenance

composition by using conventional geochemical discrimination plots. This becomes a test

to determine the extent to which, if at all, physical sorting impacts the geochemical

composition of naturally sorted clastic sediment.

More directly, this work questions whether commonly used discriminative plots

are representative of actual source compositions, and how accurate past studies that have

used bulk geochemistry to interpret the provenance of sandstones (Roser and Korsch,

1999; Armstrong-Altrin et al., 2004; Bakkiaraj et al., 2010) and mudrocks (Cullers, 2000;

Bhat and Ghosh, 2001; Lee, 2002; Hofmann et al., 2003) may be. In this study, clastic

sediments were collected from a single location in a fluvial channel where the source

composition is known. Samples span the types of grain sizes (fine pebbles to coarse silt)

that comprise the sedimentary record, and that are commonly used in provenance work. If

these samples fail to reconstruct the same, known source composition regardless of grain

size, the accuracy of using whole-rock geochemistry to interpret provenance may be

more limited by physical sorting than previously thought.

8.1 Major elements

8.1.1 A–CN–K and A–CNK–FM diagrams

In addition to evaluating chemical weathering trends, A–CN–K (Fig. 14A) and

A–CNK–FM (Fig. 14B) diagrams can also be used to infer provenance composition by

50

tracing sediment compositions parallel to the A-CN boundary back to the feldspar tie line

(Fedo et al., 1995; Nesbitt and Markovics, 1997). Although Stepladder sediment samples

were derived from the same source, sediments separated by grain-size fractions span the

compositional range between average compositions of granite, granodiorite, and diorite in

A–CN–K space (Fig. 14A). In A–CNK–FM (Fig. 14B) space, fine-grained samples plot

closer to more mafic provenances, whereas coarser samples indicate a more felsic source.

Reasoning behind these compositional variations can be supported by petrographic

observations, which revealed the preferential sorting of plagioclase and biotite in fine-

grained sediment fractions. However, interpretations of provenance using these plots

would permit a range of possible source compositions.

8.1.2 Discriminant function plots

The compositional plots of Roser and Korsch (1988) incorporate major elements

in the form of discriminant functions that distinguish between felsic, intermediate, mafic,

or quartzose sedimentary sources of sediment. These discriminant functions are based on

the oxides of TiO2, Al2O3, Fe2O3, MgO, CaO, Na2O, and K2O, which were determined by

Roser and Korsch (1988) to be the most effective at differentiating provenance.

Sediments plotted in Figure 15A designate a felsic igneous provenance, with fine-grained

sediments trending towards a more intermediate composition. To circumvent the problem

of CaO and SiO2 content derived from biogenic sources, Roser and Korsch (1988)

developed an alternative plot that uses discriminant functions based on the same major

elements, but as ratios with Al2O3. This discriminate function plot (Fig. 15B) places

bedrock within the intermediate compositional field, and fine-grained sediments trend

towards a mafic provenance.

51

Figure 15A-B. Discriminant function plots used to interpret source compositions of Stepladder sediments.

All plots and discriminant functions by Roser and Korsch (1988). (A) Discriminant function plot. DF 1 = (-

1.773*TiO2) + (0.607*Al2O3) + (0.76*Fe2O3) – (1.5*MgO) + (0.616*CaO) + (0.509*Na2O) + (-1.22*K2O)

- 0.909 and DF2 = (0.445* TiO2) + (0.07* Al2O3) – (0.25* Fe2O3) – (1.142* MgO) + (0.438* CaO) +

(0.432*Na2O) + (1.426*K2O) - 6.861 (B) Discriminant function plot correcting for biogenic CaO and SiO2.

DF1 = 30.638*(TiO2/Al2O3) - 12.541*(Fe2O3/Al2O3) + 7.329*(MgO/Al2O3) + 12.031*(Na2O/Al2O3) +

(35.402*(K2O/Al2O3) - 6.382 and DF2 = 56.5*(TiO2/Al2O3) - 10.879*(Fe2O3/Al2O3) +

30.875*(MgO/Al2O3) - 5.404*(Na2O/Al2O3) + 11.112*(K2O/Al2O3) - 3.89.

52

As sorting is likely causing these compositional variations across grain-size

populations, the utility of these plots in correctly predicting the provenance of sorted

sediments from an unknown source composition may be problematic. Despite the

compositional variations between samples, the first discriminant plot (Fig. 15A) was

successful at predicting a felsic provenance for all sediments, as well as average bedrock.

In the case of the alternative discriminative function plot (Fig. 15B), two different

igneous provenances can be interpreted across the spectrum of samples derived from the

same source. As several studies have used these plots to interpret the source composition

of transported sediments (Roser et al., 1996; Bahlburg, 1998; Roser and Korsch, 1999;

Oni et al., 2014; Armstrong-Altrin et al., 2015; Eizenhöfer et al., 2015), it should be

noted that only coarser-sized sediment fractions (between fine gravel and medium sand)

may plot near the actual source composition within an appropriate provenance field.

8.2 Trace elements

8.2.1 Incompatible to compatible element ratio plots

Trace elements are suitable for provenance interpretation in the form of ratios of

incompatible and compatible elements. To discriminate between felsic and mafic sources,

incompatible elements (La, Th, Hf, Zr) that are abundant in felsic minerals are compared

with compatible elements (Sc, Cr, Co) abundant in mafic minerals (Cullers et al., 1988).

Thus, when these trace elements of sand-sized sediments are represented as incompatible

to compatible element ratios (Th/Sc, La/Sc, Th/Co, La/Co, Cr/Th), they can indicate

provenance composition (Taylor and McLennan, 1985; Bhatia and Crook, 1986; Condie

and Wronkiewicz, 1990), and more specifically, uncover the relative contribution of

felsic to mafic inputs. However, because mineral fractionation can occur during transport

53

(Fralick and Kronberg, 1997), the use of these ratios and elements to make interpretations

of provenance are potentially only valid for locally derived sediments. In order to test if

first-cycle sediments from a known source would predict provenance, sediments were

plotted in Th/Sc vs Sc ppm, Cr/Th vs Th/Sc, and Th/Co vs La/Sc diagrams along with

Stepladder pluton and saprolite reference compositions, probable sources of Meso-

Cenozoic basalt, Phanerozoic granite, Meso-Cenozoic andesite, and tonalite-

trondhjemite-granodiorite (TTG) (Condie, 1993). All plots include reference lines on

average bedrock composition, which forms an end member mixing model with basalt.

In the Th/Sc vs Sc ppm plot (McLennan and Taylor, 1991; Fedo et al., 1996; Fig.

16A), average bedrock has a relatively high Th/Sc value of 10.66, whereas sediment

samples exhibit immediately lower Th/Sc values that range from 4.29 to 1.37 from coarse

to fine populations. The systematic decrease in Th/Sc values with decreasing grain size

occurs because the Sc contents in sediment become enriched up to thirteen times the

original bedrock Sc values, whereas Th values in sediment are only enriched up to 1.7

times the original bedrock Th values (Fig. 13A). The coarsest sample, CD-1, even

exhibits a considerably low Th/Sc ratio of 4.29, which demonstrates that small, overall

contribution of fine-grained sediment in a sample composed of mostly gravel can still

distort immobile element signatures. Despite the fact that sediment collected for this

study was sourced from a single pluton, the data scatter supports source mixing of the

average bedrock and a basaltic end member (Fig. 16A) to produce the ranges of possible

sediment compositions observed.

On the Cr/Th vs Th/Sc plot (Condie and Wronkiewicz, 1990; Condie et al., 2001;

Fig. 16B), sediments display increasing Cr/Th values with decreasing grain size. This is

54

Figure 16A-C. Incompatible to compatible trace element plots of Stepladder sediment, saprolite, and

bedrock. (A) Th/Sc vs Sc ppm diagram (B) Cr/Th vs Th/Sc diagram. Red square denotes sample CD-1 that

used Cr value from Modi (2011). Green triangle denotes sample CD-3 that used Cr value from Modi

(2011). (C) Th/Co vs La/Sc diagram. Reference compositions of average Meso-Cenozoic basalt,

Phanerozoic granite, Meso-Cenozoic andesite, and tonalite-trondhjemite-granodiorite (TTG) from Condie

(1993). Compositions of samples of the Toorongo granodiorite weathering profile (black dots) from Nesbitt

and Markovics (1997).

55

likely the result of Cr increasing in concentration across decreasing grain sizes, more so

than Th (Fig. 13A). The data scatter suggests that sediments are derived from the mixing

of greater contributions of mafic components with decreasing grain size. However, it is

unlikely that any process other than sorting caused these compositional variations.

Saprolite values plot virtually next to the composition of average bedrock, which

suggests that sediment transport and natural sorting are primarily responsible for

compositional variability.

On the Th/Co vs La/Sc plot (Cullers, 2002; Gu et al., 2002; Oni et al., 2014; Fig.

16C), bedrock and saprolite plot close to each other, whereas sediments begin to deviate

towards more mafic compositions. Thorium/cobalt values in sediments become generally

lower with decreasing grain sizes whereas La/Sc values increase. These compositional

variations can be attributed to how compatible elements, Sc and Co, become strongly

enriched with decreasing grain size, relative to the incompatible elements, Th and La

(Fig. 13A; Table 4).

Enrichment in compatible elements in fine-grained sediments indicates that the

preferential sorting of minerals comprised of these trace elements can cause considerable

shifts in provenance interpretations. Elevated transition metal concentrations can be

attributed to the “nugget effect” (Wendt and Thomas, 1990), which is caused by the

enrichment of a non-abundant mineral in a sediment sample containing trace elements

only held within that mineral (in this case, Co, Cr and Sc in biotite). Thus, preferential

sorting of biotite in fine-grained sediment sizes leads to elemental enrichments relative to

the source composition.

56

To test if chemical weathering from a similar source composition would result in

considerable departures in provenance, a selection of 12 increasingly chemically

weathered samples of Toorongo granodiorite profile (range of CIA = 50 – 99) studied in

Nesbitt and Markovics (1997) were plotted alongside the Stepladder sediments in the

diagrams of Th/Sc vs Sc ppm and Cr/Th vs Th/Sc (no cobalt reported in Toorongo

geochemical dataset, thus the Th/Co vs La/Sc plot was excluded). The trend of the

increasingly chemically weathered samples from the Toorongo weathering profile show

increasing Th/Sc ratios and Sc content with increasing CIA (Fig. 16A), which is a

different trend observed from the Stepladder samples from increased sorting. In the Cr/Th

vs Th/Sc plot (Fig. 16B), decreasing Cr/Th values correlate with increasing CIA values.

Even the most strongly chemically weathered samples of the Toorongo profile (CIA =

99) do not vary from the least weathered samples (CIA = 50) as much as the coarsest

sample CD-1 varies from average Stepladder bedrock due to sorting. Thus, using

immobile element ratios to interpret source composition of chemically weathered samples

is better suited for provenance interpretation than using sediments that have become

sorted. Such findings imply that sorting after very minimal transport can fractionate

sediments from source composition more so than chemical weathering can.

Despite being locally derived from the same source, Stepladder sediments

indicate a wide compositional range between the pluton and the mixing of a generic

basaltic end member (Fig. 16A-C), which is similar to Modi’s (2011) conclusions. Such

outcomes show that, even though immobile trace elements are thought to be

quantitatively transferred to the sedimentary record during chemical weathering (e.g.

Cullers et al., 1987, 1988; Bhatia and Taylor, 1981; Bhatia and Crook, 1986; Taylor and

57

McLennan, 1985; Cullers and Stone, 1991; McLennan et al., 1993), mineral sorting, even

after minimal transport, can cause these elements to differ from the source material. Of

important note, is that the greatest compositional deviations occur in the finest-grained

material, which challenges the accuracy of provenance work using these immobile

elements to interpret the source of mudstones (Cullers, 2000; Bhat and Ghosh, 2001; Lee,

2002; Hofmann et al., 2003). Furthermore, even the coarsest samples that most closely

should resemble bedrock composition contain enough fine-material with mafic trace

elements to cause compositional deviations from bedrock. Thus, any work using

immobile elements to interpret provenance may be strongly limited by physical sorting

regardless of what grain-size population is considered. Bearing in mind that sorting is a

process that occurs in all cases of bedload transport, and that many studies have

interpreted the provenance of sedimentary rocks or sediments that have travelled further

distances than those studied here (Cullers et al., 1988; Slack and Stevens, 1994;

Bahlburg, 1998; Bauluz et al., 2000; Roser and Korsch, 1999; Cullers and Podkovyrov,

2000; Condie et al., 2001; Gu et al., 2002; Zimmerman and Bahlburg, 2003; Oni et al.,

2014; Eizenhöfer et al., 2015; Xiang et al., 2015), the conventionally accepted notion that

certain immobile elements behave as a closed system throughout sedimentary processing

is rejected.

8.2.2 Sediment recycling ratio plots

Other trace element ratio plots, such as Th/Sc vs Zr/Sc (McLennan et al., 1993;

Fig. 17A), have been used to infer zircon enrichment by sediment recycling over a range

of compositions (Bahlburg, 1998; Roser and Korsch, 1999; Zimmerman and Bahlburg,

2003; Oni et al., 2014; Xiang et al., 2015; Moradi et al., 2016). The distribution of

58

Figure 17A-B. Plots demonstrating extent of sediment recycling. (A) Th/Sc vs Zr/Sc diagram from

McLennan et al. (1993). (B) La/Sc vs Hf ppm diagram from Floyd and Leveridge (1987).

59

Stepladder sediments plotted in the Th/Sc vs Zr/Sc diagram (Fig. 17A) indicates that the

sediments were derived from a felsic source, with Th/Sc values ranging between 1 and

10. Sediments have Zr/Sc values that range from 72.8 to 39 from coarser- to fine-grained

samples, suggesting varying degrees of recycling across samples. However, bedrock and

saprolite Zr/Sc values are much higher, equaling 274.5 and 207.5, respectively. Such

variations in the Zr/Sc ratio between sediment and bedrock are likely due to large

departures in Sc concentrations from bedrock composition compared to Zr (Fig. 13A).

However, increases in Zr/Sc values from fine to coarse samples (Fig. 17A) suggest that

the coarser samples endured sediment recycling, despite that all sediments were first

cycle materials.

Another common plot, La/Th vs Hf (Floyd and Leveridge, 1987; Fig. 17B), has

been used to recognize older sediment components formed by sediment recycling (Gu et

al., 2002; Xiang et al., 2015; Moradi et al., 2016). As La/Th is a good indicator of source

composition (Taylor and McLennan, 1985), an increasing concentration of Hf in

sediment is correlated with zircon enrichment (Floyd and Leveridge, 1987). All

sediments except for sample CD-1 correctly plot within the felsic arc source with low

La/Th values (between 0 and 5) that are characteristic of felsic compositions (Fig. 17B).

Coarser samples show relatively low Hf values, which suggests a non-recycled origin,

whereas fine-grained sediment samples have slightly higher values than coarser samples

(Fig. 17B). Interestingly, the La/Th vs Hf plot (Fig. 17B) proved to be better at matching

sediment compositions to the known source than the Th/Sc vs Zr/Sc plot (Fig. 17A),

which is because there are greater departures in Sc from average bedrock relative to those

of Zr (Fig. 13A). Thus, the ratio of Zr/Sc is likely sensitive to mineral sorting.

60

While interpretations of different source compositions and degrees of sediment

recycling can be made for the Stepladder samples, all compositional variations can likely

be attributed to mostly to physical sorting. Variations in abundances of Zr and Hf across

all the Stepladder sediments do not necessarily imply that these sediments had endured

varying degrees of recycling, but rather that zircon had become preferentially

concentrated in finer grain-size populations during minimal transport. Therefore, it must

be understood that sorting does not only hold the capacity to influence the concentrations

of transition metals in sediment, but also certain elements held within weathering-

resistant minerals.

8.3 Rare-earth elements

Rare-earth elements have been widely considered very useful indicators of

provenance under the premise that they are not easily fractionated between sediment and

source, and that sources ranging from felsic to ultramafic have distinct REE patterns

(Taylor and McLennan, 1985; Cullers, 1988; McLennan and Taylor, 1991).

Characteristics of these patterns that describe the slopes of LREEs and HREEs, as well as

the magnitude of the Eu anomaly, can be displayed as ratios (La/Sm, Gd/Yb, La/Yb,

Eu/Eu*) and have been used as indicators of provenance (Cullers and Podkovyrov, 2000;

Slack and Stevens, 1994; Bauluz et al., 2000; Condie et al., 2001; Gu et al., 2002;

Zimmerman and Bahlburg, 2003; Oni et al., 2014; Xiang et al., 2015; Armstrong-Altrin

et al., 2015; Moradi et al., 2016). Although the Stepladder sediment samples have broadly

similar bedrock-normalized REE patterns (Fig. 13B), these ratios, as well as total REE

content, depart from bedrock composition with decreasing grain size. To examine the role

61

of sorting on REE composition, each feature (∑REE, LaBN/SmBN, GdBN/YbBN) can be

comparatively discussed with Eu/Eu*BN values (Fig. 18A-C).

8.3.1 Rare-earth element plots

8.3.1.1 Total REE content

Total REE contents of Stepladder sediments increase with decreasing grain size,

resulting in sediments plotting between a range of reference compositions, with most

samples differing in composition from average bedrock (Fig. 18A). Finer-grained

samples, CD-4 and CD-5, most closely resemble the more felsic reference composition of

Meso-Cenozoic granite than the known source (Fig. 18A). Coarser-grained samples CD-2

and CD-3 most closely resemble the composition of TTG, but with marginally higher

total REE content (Fig. 18A).

Variations in REE content across grain sizes can occur as finer fractions are more

likely to be dominated by heavy minerals (Cullers et al., 1987; Cullers et al., 1988). In the

case of the Stepladder sediments, increasing total REE content with decreasing grain size

may be a result of accessory minerals concentrating in fine-grained sediment populations,

as the magnetite concentrate, CD-M, has vastly more REE content (∑REE = 4873.4 ppm)

than any other sample. Zircon concentration may also be a factor, as abundances of both

Zr and Hf increase from coarse to fine samples (Fig. 13A).

8.3.1.2 Europium anomaly

Four of the sediment samples have a negative Eu anomaly, with Eu/Eu*BN values

that range from 0.72 to 0.61 (CD-2 through CD-5; Table 5). The coarsest sediment

sample, CD-1, exhibits a slightly positive Eu/Eu*BN value of 1.02. Bedrock and saprolite

62

Figure 18A-C. Bedrock-normalized Eu/Eu* plots. All plots from McLennan (1989). (A) REE Total vs Eu

anomaly (B) La/Sm vs Eu anomaly (C) Gd/Yb vs Eu anomaly. Reference compositions of average Meso-

Cenozoic basalt, Phanerozoic granite, and tonalite-trondhjemite-granodiorite (TTG) from Condie (1993).

63

Eu/Eu*BN values are 1.00 and 1.03, respectively, illustrating that a negative europium

signature is developed as soon as sediment becomes sorted as coarse sand.

As the magnetite concentrate, sample CD-M, has a strongly negative Eu/Eu*BN

value (Fig. 18B-C), it can be suggested that the preferential sorting of magnetite in finer

grain sizes may partly influence the europium signature. It is also possible that zircon

enrichment in finer grain-size fractions somewhat controls the Eu anomaly as zircons

commonly have depleted Eu signatures relative to Sm and Gd (Trail et al., 2012). This is

problematic, however, as pioneering provenance work considers the negative Eu

signature to be inherited from a more felsic source than granodiorite (McLennan et al.,

1993). As sediments collected in this study range from having no Eu anomaly to a

negative one, the value of Eu/Eu* in sorted sediment fractions finer than coarse sand may

not necessarily reflect true source composition.

8.3.1.3 LREE and HREE content

Fractionation of LREEs decreases with decreasing grain size (Fig. 18B;

LaBN/SmBN = 1.13 for CD-1 to 0.76 for CD-5). Heavy REE fractionation also decreases

from coarse to fine sediments (Fig. 18C; GdBN/YbBN = 0.93 for CD-1 to 0.67 for CD-5).

Decreasing fractionations of both LREEs and HREEs may be due to an enrichment of

certain accessory minerals across all samples. However, it is unclear if magnetite may

control fractionation behavior, as sample CD-M does not exhibit similar slopes for

LREEs and HREEs (Fig. 13C), nor does it have LaBN/SmBN (Fig. 18B) or GdBN/YbBN

(Fig. 18C) values that show a correlation with decreasing grain size. Conversely, zircon,

which increases in abundance with decreasing grain-size fractions (Table 2), may be

64

responsible for the behavior of increasing HREE slopes as it commonly has high HREE

content (Borges et al. 2008; Mahjoor et al., 2009).

For both LREEs and HREEs, finer-grained sediments trend toward more felsic

compositions (Fig. 18B-C). Interestingly, this opposes the data scatter in the incompatible

to compatible trace element plots (Fig. 16A-C), which indicated finer-grained sediments

trend toward more mafic compositions. Such a finding illustrates that there are

inconsistencies between interpretations of source composition that can be made,

depending on which elements are considered. Consequently, the utility of trace and rare-

earth elements as reliable indicators of provenance may be strongly challenged by the

impact physical sorting has on sediment composition.

65

9. SUMMARY AND CONCLUSIONS

1. The goal of this study was to test the effectiveness of commonly used

geochemical and petrographic techniques applied to provenance interpretations

for sediment produced from a known source and subsequently sorted during

minimal fluvial transport. The Stepladder Mountains in the Mojave Desert, CA,

reside in an arid setting where modern sediments within an enclosed drainage

basin should ideally resemble the single, known source because of essentially

minimal chemical weathering and transport. Previous work by Modi (2011) has

shown that sediments are naturally sorted by grain size in fluvial channels that

dissect the source region. The hypothesis tested was that if sediments could be

substantially sorted by grain size after only meters of transport in an arid climate,

then they would exhibit mineralogical and thus, geochemical deviations from the

known source.

2. Within the watershed, five sediment samples were collected across a single

channel and had become sorted into five distinct grain-size populations. Every

sediment sample, despite mean grain size differences, comprised the same

mineralogy as the granitic bedrock, which consisted of plagioclase, K-feldspar,

quartz, and biotite. Accessory minerals include magnetite, apatite, and zircon.

Coarser sediments (CD-1 and CD-2) were enriched in quartz, whereas fine-grain

sediments (CD-3, CD-4, and CD-5) were enriched in plagioclase, biotite, and

magnetite.

3. The low CIA values in both sediment and bedrock indicate that the degree of

chemical weathering influencing sediment composition is negligible. However,

66

data suggest that if a small amount weathering products were present, they are

concentrated in finer grain sizes. Fractionation of FeO and MgO from Al2O3,

CaO, Na2O, and K2O occurs during transport, and biotite and magnetite were

concentrated in fine-grained samples.

4. Trace-element plots normalized to average bedrock show strong departures in Cr,

Co, and Sc which are thought to be immobile during sedimentary processing, and

thus are commonly used as components in provenance discriminating ratios.

Sediment ratios successfully interpret the felsic source composition of the

bedrock. However, fine-grained samples reveal preferential trends toward mafic

compositions. Several trace-element ratios, La/Sc, Th/Sc, Th/Co reveal that

sediment may have acquired its composition from the mixing of a basaltic

compositional end member with the actual source to produce the composition of

the fine-grained sediment. Samples of the fresh and chemically weathered

components of a weathering profile indicated that sorting has a greater effect on

distorting the expected outcomes of ratios using immobile elements than chemical

weathering does. Particular diagrams, Th/Sc vs Zr/Sc and La/Th vs Hf ppm,

successfully indicate that appreciable sediment recycling has not occurred, but

demonstrate any ratios using supposedly immobile elements, such as Sc, cause

sediments to deviate from source composition. Coarser samples had greater Zr/Sc

ratios, and thus appeared to have undergone greater sediment recycling than fine-

grained samples.

5. Rare-earth element patterns normalized to average bedrock show that sediments

with decreasing grain sizes have increasingly greater total REE content, negative

67

Eu anomalies, and fractionated LREE and HREE slopes. High rare-earth element

contents of the magnetite concentrate, sample CD-M, suggest that increasing

proportions of magnetite in fine-grained samples may control total REE content.

Variations in the strength of the Eu anomaly, as well as the LREE and HREE

contents across samples, may be controlled by accessory mineral concentration as

magnetite, zircon, and apatite increase in modal abundance in the finer grain

sizes.

6. Despite that the diagrams used in this study are thought to be insensitive to

sedimentary processing, the only factor responsible for causing the composition

of these sediment samples to deviate from another or bedrock is mineral sorting

during less than 0.1 km of transport. This work shows that sediment sorting is

capable of inducing compositional and geochemical changes between source and

sediment, even within trace elements, and that these changes begin to take effect

immediately within the source terrain. Therefore, the ability to accurately

reconstruct provenance from sediment deposited at any distance from the source

rock may be more problematic than previously recognized. Henceforth,

provenance evaluation should consider the influence of fluvial sorting on

sediment composition.

68

REFERENCES CITED

69

Anderson, J.L. and Bender, E.E., 1989. Nature and origin of Proterozoic A-type granitic

magmatism in the southwestern United States of America. Lithos, v. 23, no. 1, p. 19-52.

Anderson, J.L. and Cullers, R.L., 1990. Middle to upper crustal plutonic construction of a

magmatic arc; an example from the Whipple Mountains metamorphic core

complex. Geological Society of America Memoirs, v. 174, p. 47-70.

Armstrong-Altrin, J. S., Lee, Y. I., Verma, S. P., and Ramasamy, S., 2004. Geochemistry

of sandstones from the upper Miocene Kudankulam Formation, southern India:

Implications for provenance, weathering, and tectonic setting. Journal of Sedimentary

Research, v. 74, no. 2, p. 285-297.

Armstrong-Altrin, J.S., Machain-Castillo, M.L., Rosales-Hoz, L., Carranza-Edwards, A.,

Sanchez-Cabeza, J.A. and Ruíz-Fernández, A.C., 2015. Provenance and depositional

history of continental slope sediments in the Southwestern Gulf of Mexico unraveled by

geochemical analysis. Continental Shelf Research, v. 95, p. 15-26.

Bahlburg, H., 1998. The geochemistry and provenance of Ordovician turbidites in the

Argentine Puna. Geological Society, London, Special Publications, v. 142, no. 1, p. 127-

142.

Bakkiaraj, D., Nagendra, R., Nagarajan, R. and Armstrong-Altrin, J.S., 2010.

Geochemistry of sandstones from the Upper Cretaceous Sillakkudi Formation, Cauvery

Basin, southern India: implication for provenance. Journal of the Geological Society of

India, v. 76, no. 5, p. 453-467.

Basu, A.R., 1976. Petrology of Holocene fluvial sand derived from plutonic source rocks;

implications to paleoclimatic interpretation. Journal of Sedimentary Research, v. 46, p.

694–709.

Basu, A., 1985. Influence of climate and relief on compositions of sands released at

source areas. In Provenance of Arenites, Springer Netherlands, v. C-148, p. 1-18.

Bauluz, B., Mayayo, M.J., Fernandez-Nieto, C. and Lopez, J.M.G., 2000. Geochemistry

of Precambrian and Paleozoic siliciclastic rocks from the Iberian Range (NE Spain):

implications for source-area weathering, sorting, provenance, and tectonic

setting. Chemical Geology, v. 168, no. 1, p. 135-150.

Bhat, M.I. and Ghosh, S.K., 2001. Geochemistry of the 2.51 Ga old Rampur Group

pelites, western Himalayas: implications for their provenance and weathering.

Precambrian Research., v. 108, p. 1-16.

Bhatia, M.R., 1983. Plate tectonics and geochemical composition of sandstones. The

Journal of Geology, v. 91, p. 611-627.

70

Bhatia, M. R., and Crook, K. A., 1986. Trace element characteristics of graywackes and

tectonic setting discrimination of sedimentary basins. Contributions to mineralogy and

petrology, v. 92, no. 2, p. 181-193.

Blott, S.J. and Pye, K., 2001. GRADISTAT: a grain size distribution and statistics

package for the analysis of unconsolidated sediments. Earth Surface Processes and

Landforms, v. 26, p. 1237-1248.

Borges, J.B., Huh, Y., Moon, S. and Noh, H., 2008. Provenance and weathering control

on river bed sediments of the eastern Tibetan Plateau and the Russian Far East. Chemical

Geology, v. 254, no. 1, p.52-72.

Braun, J.J. and Pagel, M., 1994. Geochemical and mineralogical behavior of REE, Th

and U in the Akongo lateritic profile (SW Cameroon). Catena, v. 21, no. 2, p.173-177.

Condie, K.C., Noll, P.D. and Conway, C.M., 1992. Geochemical and detrital mode

evidence for two sources of Early Proterozoic sedimentary rocks from the Tonto Basin

Supergroup, central Arizona. Sedimentary Geology, v. 77, no. 1, p. 51-76.

Condie, K.C., Lee, D. and Farmer, G.L., 2001. Tectonic setting and provenance of the

Neoproterozoic Uinta Mountain and Big Cottonwood groups, northern Utah: constraints

from geochemistry, Nd isotopes, and detrital modes. Sedimentary Geology, v. 141, p.

443-464.

Condie, K.C. and Wronkiewicz, D.J., 1990. The Cr/Th ratio in Precambrian pelites from

the Kaapvaal Craton as an index of craton evolution. Earth and Planetary Science Letters

v. 97, p. 256–267.

Condie, K.C., 1993. Chemical composition and evolution of the upper continental crust:

contrasting results from surface samples and shales. Chemical geology, v. 104, no. 1, p.

1-37.

Cox, K.G., Bell, J.D. and Pankhurst, R.J., 1979. The Interpretation of Igneous Rocks,

Springer Netherlands, p. 42-82.

Cullers, R., 1988. Mineralogical and chemical changes of soil and stream sediment

formed by intense weathering of the Danburg granite, Georgia, USA. Lithos, v. 21, no. 4,

p. 301-314.

Cullers, R. L., 1994. The chemical signature of source rocks in size fractions of Holocene

stream sediment derived from metamorphic rocks in the wet mountains region, Colorado,

USA. Chemical Geology, v. 113, no. 3, p. 327-343.

Cullers, R.L., 2000. The geochemistry of shales, siltstones and sandstones of

Pennsylvanian– Permian age, Colorado, USA: implications for provenance and

metamorphic studies. Lithos, v. 51, p. 181– 203.

71

Cullers, R. L., 2002. Implications of elemental concentrations for provenance, redox

conditions, and metamorphic studies of shales and limestones near Pueblo, CO,

USA. Chemical Geology, v. 191, no. 4, p. 305-327.

Cullers, R.L., Barrett, T., Carlson, R. and Robinson, B., 1987. Rare-earth element and

mineralogic changes in Holocene soil and stream sediment: a case study in the Wet

Mountains, Colorado, USA. Chemical geology, v. 63, no. 3, p. 275-297.

Cullers, R.L., Basu, A. and Suttner, L.J., 1988. Geochemical signature of provenance in

sand-size material in soils and stream sediments near the Tobacco Root batholith,

Montana, USA. Chemical Geology, v. 70, no. 4, p. 335-348.

Cullers, R.L. and Podkovyrov, V.N., 2000. Geochemistry of the Mesoproterozoic

Lakhanda shales in southeastern Yakutia, Russia: implications for mineralogical and

provenance control, and recycling. Precambrian Research, v. 104, no. 1, p. 77-93.

Cullers, R.L. and Stone, J., 1991. Chemical and mineralogical comparison of the

Pennsylvanian Fountain Formation, Colorado, USA (an uplifted continental block) to

sedimentary rocks from other tectonic environments. Lithos, v. 27. no. 2, p. 115-131.

DeWitt, E.D., Armstrong, R.L., Sutter, J.F. and Zartman, R.E., 1984. U-Th-Pb, Rb-Sr,

and Ar-Ar mineral and whole-rock isotopic systematics in a metamorphosed granitic

terrane, southeastern California. Geological Society of America Bulletin, v. 95, no. 6, p.

723-739.

Dickinson, W.R., 1970. Interpreting detrital modes of graywacke and arkose. Journal of

Sedimentary Petrology, v. 40, p. 695–707.

Dickinson, W.R., Beard, L.S., Brakenridge, G.R., Erjavec, J.L., Ferguson, R.C., Inman,

K.F., Knepp, R.A., Lindberg, F.A. and Ryberg, P.T., 1983. Provenance of North

American Phanerozoic sandstones in relation to tectonic setting. Geological Society of

America Bulletin, v. 94, no. 2, p. 222-235.

Dickinson, W.R. and Suczek, C.A., 1979. Plate tectonics and sandstone compositions.

The American Association of Petroleum Geologists Bulletin, v. 63, p. 2164–2182.

Dickinson, W. R., and Valloni, R., 1980. Plate settings and provenance of sands in

modern ocean basins. Geology, v. 8, no. 2, p. 82-86.

Dickinson, W. R., Beard, L. S., Brakenridge, G. R., Erjavec, J. L., Ferguson, R. C.,

Inman, K. F., and Ryberg, P. T., 1983. Provenance of North American Phanerozoic

sandstones in relation to tectonic setting. Geological Society of America Bulletin, v. 94,

no. 2, p. 222-235.

72

Dohrenwend, J. C., 1988. Age of the formation and evolution of pediment domes in the

area of the Cima volcanic field, Mojave Desert, California. In This extended land:

geological journeys in the Southern Basin and Range: field trip guidebook, Geological

Society of America, Cordilleran Section Meeting, Las Vegas, Nevada, 1988, p. 214.

Eizenhöfer, P.R., Zhao, G., Zhang, J., Han, Y., Hou, W., Liu, D. and Wang, B., 2015.

Geochemical characteristics of the Permian basins and their provenances across the

Solonker Suture Zone: assessment of net crustal growth during the closure of the Palaeo-

Asian Ocean. Lithos, v. 224, p. 240-255.

Fedo, C.M., Nesbitt, H.W. and Young, G.M., 1995. Unraveling the effects of potassium

metasomatism in sedimentary rocks and paleosols, with implications for paleoweathering

conditions and provenance. Geology, v. 23, no. 10, p. 921-924.

Fedo, C.M., Eriksson, K.A. and Krogstad, E.J., 1996. Geochemistry of shales from the

Archean (~ 3.0 Ga) Buhwa Greenstone Belt, Zimbabwe: implications for provenance and

source-area weathering. Geochimica et Cosmochimica Acta, v. 60, no. 10, p. 1751-1763.

Fedo, C.M. and Cooper, J.D., 2001. Sedimentology and sequence stratigraphy of

Neoproterozoic and Cambrian units across a craton-margin hinge zone, southeastern

California, and implications for the early evolution of the Cordilleran

margin. Sedimentary Geology, v. 141, p. 501-522.

Fedo, C.M., McGlynn, I.O. and McSween, H.Y., 2015. Grain size and hydrodynamic

sorting controls on the composition of basaltic sediments: Implications for interpreting

martian soils. Earth and Planetary Science Letters, v. 423, p. 67-77.

Feng, R. and Kerrich, R., 1990. Geochemistry of fine-grained clastic sediments in the

Archean Abitibi greenstone belt, Canada: implications for provenance and tectonic

setting. Geochimica et Cosmochimica Acta, v. 54, no. 4, p. 1061-1081.

Floyd, P.A. and Leveridge, B.E., 1987. Tectonic environment of the Devonian

Gramscatho basin, south Cornwall: framework mode and geochemical evidence from

turbiditic sandstones. Journal of the Geological Society, v. 144, no. 4, p. 531-542.

Folk, R.L., 1955. Student operator error in determination of roundness, sphericity, and

grain size. Journal of Sedimentary Research, v. 25, no. 4, p. 297-301.

Folk, R.L., 1974. Petrology of sedimentary rocks. Texas (Hemphill Publishing Co.). 182

p.

Folk, R.L. and Ward, W.C., 1957. Brazos River bar: a study in the significance of grain-

size parameters. Journal of Sedimentary Research, v. 27, no. 1, p. 3-32.

Fralick, P. W., and Kronberg, B. I. 1997. Geochemical discrimination of clastic

sedimentary rock sources. Sedimentary Geology, v. 113, no. 1, p. 111-124.

73

Gu, X.X., Liu, J.M., Zheng, M.H., Tang, J.X. and Qi, L., 2002. Provenance and tectonic

setting of the Proterozoic turbidites in Hunan, South China: geochemical

evidence. Journal of sedimentary Research, v. 72, no. 3, p. 393-407.

Hofmann, A., Bolhar, R., Dirks, P. and Jelsma, H., 2003. The Geochemistry of Archean

shales derived from a mafic volcanic sequence, Belingwe greenstone belt, Zimbabwe:

Provenance, source area unroofing and submarine versus subaerial weathering. Geochim.

Cosmochim. Acta, v. 67, p. 421-440.

Holail, H.M. and Moghazi, A.K.M., 1998. Provenance, tectonic setting and geochemistry

of greywackes and siltstones of the Late Precambrian Hammamat Group,

Egypt. Sedimentary Geology, v. 116, no. 3, p. 227-250.

Howard, K.A. and John, B.E., 1987. Crustal extension along a rooted system of imbricate

low-angle faults: Colorado River extensional corridor, California and

Arizona. Geological Society, London, Special Publications, v. 28, no. 1, p. 299-311.

Ingersoll, R. V., Bullard, T. F., Ford, R. L., Grimm, J. P., Pickle, J. D., and Sares, S. W.,

1984. The effect of grain size on detrital modes: a test of the Gazzi-Dickinson point-

counting method. Journal of Sedimentary Research, v. 54, no. 1, p. 103-116.

Johnsson, M. J., 1993. The system controlling the composition of clastic

sediments. Geological Society of America Special Papers, v. 284, p. 1-20.

Lawrence, M.G. and Kamber, B.S., 2006. The behaviour of the rare earth elements

during estuarine mixing—revisited. Marine Chemistry, v. 100, no. 1, p. 147-161.

Lee, Y., II., 2002. Provenance derived from the geochemistry of the Palaeozoic-early

Mesozoic mudrocks of the Pyeongan Supergroup, Korea. Sedimentary Geol., v. 149, p.

219- 235

Mahjoor, A.S., Karimi, M. and Rastegarlari, A., 2009. Mineralogical and geochemical

characteristics of clay deposits from South Abarkouh district of clay deposit (Central

Iran) and their applications. Journal of Applied Sciences, v. 9, no. 4, p. 601-614.

McDonald, E. V., McFadden, L. D., and Wells, S. G., 2003. Regional response of alluvial

fans to the Pleistocene-Holocene climatic transition, Mojave Desert, California. Special

papers – Geological Society of America, v. 368, p. 189-206.

McDonough, W.F. and Sun, S.S., 1995. The composition of the Earth. Chemical

geology, v. 120, no. 3, p. 223-253.

McLennan, S. M., 1989. Rare earth elements in sedimentary rocks; influence of

provenance and sedimentary processes. Reviews in Mineralogy and Geochemistry, v. 21,

no. 1, p. 169-200.

74

McLennan, S.M., 2001. Relationships between the trace element composition of

sedimentary rocks and upper continental crust. Geochemistry, Geophysics,

Geosystems, v. 2, doi:10.1029/2000GC000109.

McLennan, S. M. and Taylor, S. R., 1991. Sedimentary rocks and crustal evolution:

tectonic setting and secular trends. The Journal of Geology, v. 99, p. 1-21.

McLennan, S. M., Hemming, S., McDaniel, D. K., and Hanson, G. N., 1993.

Geochemical approaches to sedimentation, provenance, and tectonics. Geological Society

of America Special Papers, v. 284, p. 21-40.

Miller, C.F. and Wooden, J.L., 1994. Anatexis, hybridization and the modification of

ancient crust: Mesozoic plutonism in the Old Woman Mountains area,

California. Lithos, v. 32, no. 1, p. 111-133.

Miyashiro, A., 1974. Volcanic rock series in island arcs and active continental

margins. American Journal of Science, v. 274, no. 4, p. 321-355.

Modi, A. L., 2011. Processes controlling the composition of first-cycle sediments

deposited in an arid-climate, with implications for provenance reconstruction studies.

Moradi, A.V., Sarı, A. and Akkaya, P., 2016. Geochemistry of the Miocene oil shale

(Hançili Formation) in the Çankırı-Çorum Basin, Central Turkey: Implications for

Paleoclimate conditions, source–area weathering, provenance and tectonic

setting. Sedimentary Geology. v. 341, p. 289-303.

Nesbitt, H. W., and Markovics, G., 1980. Chemical processes affecting alkalis and

alkaline earths during continental weathering. Geochimica et Cosmochimica Acta, v. 44,

no. 11, p. 1659-1666.

Nesbitt, H.W. and Markovics, G., 1997. Weathering of granodioritic crust, long-term

storage of elements in weathering profiles, and petrogenesis of siliciclastic

sediments. Geochimica et Cosmochimica Acta, v. 61, no. 8, p. 1653-1670.

Nesbitt, H.W. and Young, G.M., 1982. Early Proterozoic climates and plate motions

inferred from major element chemistry of lutites. Nature, v. 299, no. 5885, p. 715-717.

Nesbitt, H.W. and Young, G.M., 1984. Prediction of some weathering trends of plutonic

and volcanic rocks based on thermodynamic and kinetic considerations. Geochimica et

Cosmochimica Acta, v. 48, no. 7, p. 1523-1534.

Nesbitt, H.W. and Young, G.M., 1989. Formation and diagenesis of weathering

profiles. The Journal of Geology, v. 97, p. 129-147.

75

Nesbitt, H.W. and Young, G.M., 1996. Petrogenesis of sediments in the absence of

chemical weathering: effects of abrasion and sorting on bulk composition and

mineralogy. Sedimentology, v. 43, no. 2, p. 341-358.

Nichols, K.K., Bierman, P.R., Hooke, R.L., Clapp, E.M. and Caffee, M., 2002.

Quantifying sediment transport on desert piedmonts using 10 Be and 26Al. Geomorphology, v. 45, no. 1, p. 105-125.

Nichols, K.K., Bierman, P.R., Caffee, M., Finkel, R. and Larsen, J., 2005.

Cosmogenically enabled sediment budgeting. Geology, v. 33, no. 2, p. 133-136.

Oni, S.O., Olatunji, A.S. and Ehinola, O.A., 2014. Determination of Provenance and

Tectonic Settings of Niger Delta Clastic Facies Using Well-Y, Onshore Delta State,

Nigeria. Journal of Geochemistry, v. 2014, Article ID 960139.

Peacock, M.A., 1931. Classification of igneous rock series. The Journal of Geology. v.

39, p. 54-67

Powers, M.C., 1953. A new roundness scale for sedimentary particles. Journal of

Sedimentary Petrology, v. 23, p. 117-119.

Roser, B.P. and Korsch, R.J., 1988. Provenance signatures of sandstone-mudstone suites

determined using discriminant function analysis of major-element data. Chemical

geology, v. 67, no. 1, p. 119-139.

Roser, B.P. and Korsch, R.J., 1999. Geochemical characterization, evolution and source

of a Mesozoic accretionary wedge: the Torlesse terrane, New Zealand. Geological

Magazine, v. 136, no. 5, p. 493-512.

Roser, B.P., Cooper, R.A., Nathan, S. and Tulloch, A.J., 1996. Reconnaissance sandstone

geochemistry, provenance, and tectonic setting of the lower Paleozoic terranes of the

West Coast and Nelson, New Zealand.New Zealand Journal of Geology and

Geophysics, v. 39, no. 1, p. 1-16.

Schoenborn, W.A., Fedo, C.M. and Farmer, G.L., 2012. Provenance of the

Neoproterozoic Johnnie Formation and Stirling Quartzite, southeastern California,

determined by detrital zircon geochronology and Nd isotope geochemistry. Precambrian

Research, v. 206, p. 182-199.

Shand, S.J., 1943. Eruptive rocks: Their genesis, composition, and classification, with a

chapter on meteorites. J. Wiley and sons, Incorporated.

Singh, P., 2009. Major, trace and REE geochemistry of the Ganga River sediments:

influence of provenance and sedimentary processes. Chemical Geology, v. 266, no. 3, p.

242-255.

76

Slack, J.F. and Stevens, B.P., 1994. Clastic metasediments of the early Proterozoic

Broken Hill Group, New South Wales, Australia: geochemistry, provenance, and

metallogenic significance. Geochimica et Cosmochimica Acta, v. 58, no. 17, p. 3633-

3652.

Stoffer, P.W., 2004. Desert landforms and surface processes in the Mojave National

Preserve and Vicinity, no. 2004-1007.

Streckeisen, A., 1976. To each plutonic rock its proper name. Earth-science reviews, v.

12, no. 1, p. 1-33.

Suttner, L. J., Basu, A., and Mack, G. H., 1981. Climate and the origin of quartz

arenites. Journal of Sedimentary Research, v. 51, no. 4, p. 1235-1246.

Tang, Y., Sang, L., Yuan, Y., Zhang, Y. and Yang, Y., 2012. Geochemistry of Late

Triassic pelitic rocks in the NE part of Songpan-Ganzi Basin, western China:

Implications for source weathering, provenance and tectonic setting. Geoscience

Frontiers, v. 3, no. 5, p. 647-660.

Taylor, S. R., and McLennan, S. M., 1985. The continental crust: its composition and

evolution. Blackwell, Oxford, p. 312.

Thomas, W.M., Clark, H.S., Young, E.D., Orrell, S.E. and Anderson, J.L., 1988.

Proterozoic high-grade metamorphism in the Colorado River region, Nevada, Arizona,

and California. Metamorphism and crustal evolution of the western United States,

Rubey, v. 7, p. 526-537.

Trail, D., Watson, E.B. and Tailby, N.D., 2012. Ce and Eu anomalies in zircon as proxies

for the oxidation state of magmas. Geochimica et Cosmochimica Acta, v. 97, p.70-87.

Wendt, C.J., and Thomas, S.W., 1990. Placer sampling and reserve estimation, in

Kennedy, B.A., ed., Surface mining (2d ed.): Littleton, Colo., Society for Mining,

Metallurgy, and Exploration, Inc., p. 1194.

Wentworth, C.K., 1922. A scale of grade and class terms for clastic sediments. The

Journal of Geology, v. 30, no. 5, p.377-392.

Wooden, J.L. and Miller, D.M., 1990. Chronologic and isotopic framework for Early

Proterozoic crustal evolution in the eastern Mojave Desert region, SE California. Journal

of Geophysical Research: Solid Earth, v. 95, no. B12, p. 20133-20146.

Wronkiewicz, D.J. and Condie, K.C., 1987. Geochemistry of Archean shales from the

Witwatersrand Supergroup, South Africa: source-area weathering and

provenance. Geochimica et Cosmochimica Acta, v. 51, no. 9, p. 2401-2416.

77

Xiang, Z., Yan, Q., White, J.D., Song, B. and Wang, Z., 2015. Geochemical constraints

on the provenance and depositional setting of Neoproterozoic volcaniclastic rocks on the

northern margin of the Yangtze Block, China: implications for the tectonic evolution of

the northern margin of the Yangtze Block. Precambrian Research, v. 264, p. 140-155.

Young, G. M., and Nesbitt, H. W., 1998. Processes controlling the distribution of Ti and

Al in weathering profiles, siliciclastic sediments and sedimentary rocks. Journal of

Sedimentary Research, v. 68, no. 3, p. 448-455.

Zimmermann, U. and Bahlburg, H., 2003. Provenance analysis and tectonic setting of the

Ordovician clastic deposits in the southern Puna Basin, NW

Argentina. Sedimentology, v. 50, no. 6, p. 1079-1104.

78

APPENDICES

79

Appendix A

Sample Images

80

Figure A 1. Photomicrographs of Stepladder bedrock.

81

Figure A 2. Photomicrographs of Stepladder saprolite.

82

Figure A 3. Loose sediment from sample CD-1.

83

Figure A 4. Photomicrographs of sample CD-1.

84

Figure A 5. Loose sediment from sample CD-2.

85

Figure A 6. Photomicrographs of sample CD-2.

86

Figure A 7. Loose sediment from sample CD-3.

87

Figure A 8. Photomicrographs of sample CD-3.

88

Figure A 9. Loose sediment from sample CD-4.

89

Figure A 10. Photomicrographs of sample CD-4.

90

Figure A 11. Loose sediment from sample CD-5.

91

Figure A 12. Photomicrographs of sample CD-5.

92

Figure A 13. Field photographs of magnetite concentrate sample CD-M in channel.

93

Figure A 14. Loose sediment from sample CD-M.

94

Appendix B

Joint Measurements

95

Table B 1. Measurements of joint set orientations taken across watershed.

NE Strike/Steep Dip NW Strike/Steep Dip NE Strike/NW Dip

Strike Dip Dip Quad Strike Dip Dip Quad Strike Dip Dip Quad

70 83 S 300 89 N 220 36 W

50 80 S 300 87 N 219 33 W

70 70 S 320 64 E 230 40 N

40 89 E 330 79 E

33 90 E 310 69 N

30 72 E 340 80 E

27 72 E 300 76 N

61 90 S 280 85 N

50 70 S 297 90 N

50 82 S 285 90 N

45 89 E 290 74 N

30 70 E 295 46 N

76 75 S 345 70 E

30 88 E 335 87 E

30 90 E 295 90 N

65 85 S 335 70 E

77 80 S 310 56 N

20 56 E 290 72 N

75 77 S 280 85 N

75 67 S

83 90 S

85 87 S

75 87 S

25 77 E

30 72 E

40 82 E

72 77 S

88 90 S

72 90 S

25 75 E

50 90 S

60 90 S

45 82 E

70 83 S

60 74 S

96

Appendix C

Sieving Data

97

Figure C 1. Grain-size overlays of samples CD-1 and CD-3 with samples from Modi (2011) with similar

grain-size distributions.

98

Figure C 2. Gravel-Mud-Sand textural classification diagram plotting channel sediments.

99

Table C 1. Sieve data for each sediment sample CD-1 through CD-5, and CD-M.

CD-1 CD-2 CD-3

Phi Indiv. % Cumu. % Wt (g) Phi Indiv. % Cumu. % Wt (g) Phi Indiv. % Cumu. % Wt (g)

-2 31.40 31.40 245.14 -2 38.07 38.07 289.89 -2 0.47 0.47 2.61

16.39 47.79 127.98 11.93 50.01 90.88 0.55 1.03 3.02

-1 16.47 64.27 128.63 -1 8.93 58.95 68.01 -1 1.27 2.30 6.94

13.00 77.27 101.5 6.84 65.79 52.1 2.85 5.15 15.53

0 7.95 85.22 62.08 0 4.76 70.55 36.26 0 6.72 11.87 36.62

4.91 90.14 38.35 4.03 74.59 30.7 13.54 25.42 73.79

1 3.00 93.14 23.42 1 4.16 78.75 31.7 1 23.17 48.59 126.24

2.09 95.23 16.38 4.41 83.16 33.6 24.55 73.14 133.76

2 1.56 96.80 12.23 2 4.37 87.54 33.29 2 15.58 88.73 84.93

0.98 97.79 7.69 3.41 90.95 26.02 6.64 95.37 36.18

3 0.67 98.46 5.26 3 2.65 93.61 20.19 3 2.61 97.99 14.24

0.49 98.96 3.88 1.92 95.53 14.67 0.95 98.94 5.21

4 0.38 99.34 2.98 4 1.58 97.12 12.05 4 0.50 99.44 2.73

0.28 99.62 2.23 1.08 98.20 8.26 0.26 99.71 1.46

5 0.37 100 2.89 5 1.79 100 13.65 5 0.28 100 1.55

Total 780.64 Total 761.27 Total 544.81

CD-4 CD-5 CD-M

Phi Indiv. % Cumu. % Wt (g) Phi Indiv. % Cumu. % Wt (g) Phi Indiv. % Cumu. % Wt (g)

-2 0.30 0.30 0.99 -2 0 0 0 -2 0.31 0.31 0.63

0.18 0.48 0.61 0 0 0 0.64 0.95 1.28

-1 0.34 0.83 1.15 -1 0 0 0 -1 1.22 2.18 2.43

0.38 1.22 1.27 0.01 0.01 0.03 2.01 4.19 4.01

0 0.66 1.88 2.18 0 0.01 0.02 0.06 0 2.91 7.10 5.8

1.20 3.08 3.95 0.03 0.06 0.12 4.38 11.49 8.73

1 3.25 6.34 10.71 1 0.12 0.19 0.43 1 6.90 18.39 13.74

8.61 14.96 28.34 0.48 0.67 1.62 10.80 29.20 21.51

2 18.52 33.48 60.9 2 1.67 2.35 5.6 2 25.21 54.42 50.20

22.63 56.11 74.42 4.85 7.20 16.19 31.06 85.48 61.83

3 18.77 74.88 61.72 3 13.64 20.84 45.54 3 12.59 98.08 25.08

11.47 86.36 37.73 23.01 43.85 76.81 1.52 99.60 3.03

4 7.067 93.43 23.24 4 24.76 68.61 82.66 4 0.24 99.84 0.48

3.59 97.02 11.81 16.25 84.87 54.25 0.07 99.92 0.15

5 2.97 100 9.79 5 15.12 100 50.5 5 0.075 100 0.15

Total 328.81 Total 333.81 Total 199.05

100

Table C 2. Textural data output from GRADISTAT program by Blott and Pye, 2001.

CD-1 CD-2 CD-3 CD-4 CD-5 CD-M

SIEVING

ERROR (%):

0.1 0.2 0.0 0.2 0.1 0.2

SAMPLE

TYPE:

Bimodal, Poorly

Sorted

Unimodal, Poorly

Sorted

Unimodal, Moderately

Sorted

Unimodal, Moderately

Sorted

Unimodal, Moderately

Sorted

Unimodal, Moderately

Sorted

TEXTURAL

GROUP:

Sandy

Gravel

Sandy

Gravel

Slightly

Gravelly Sand

Slightly

Gravelly Sand

Muddy Sand Slightly

Gravelly Sand

SEDIMENT

NAME:

Sandy

Very Fine Gravel

Sandy Fine

Gravel

Slightly

Very Fine Gravelly

Medium

Sand

Slightly

Very Fine Gravelly

Fine Sand

Very Coarse

Silty Very Fine Sand

Slightly

Very Fine Gravelly

Fine Sand

Folk and

Ward

Method

(Φ)

Mean (x̄) -1.24454 -0.7258 1.008309 2.414867 3.620854 1.728942

Sorting (σ) 1.123465 1.841119 0.872632 0.980041 0.794267 0.894991

Skewness (Sk) 0.365226 0.632267 -0.0385 0.099876 -0.0101 -0.37022

Kurtosis (K) 1.034581 0.871386 1.128224 1.130148 0.953712 1.304965

Descriptions Mean (x̄) Very Fine Gravel

Very Coarse Sand

Medium Sand

Fine Sand Very Fine Sand

Medium Sand

Sorting (σ) Poorly

Sorted

Poorly

Sorted

Moderately

Sorted

Moderately

Sorted

Moderately

Sorted

Moderately

Sorted

Skewness (Sk) Very Fine Skewed

Very Fine Skewed

Symmetrical Symmetrical Symmetrical Very Coarse

Skewed

Kurtosis (K) Mesokurtic Platykurtic Leptokurtic Leptokurtic Mesokurtic Leptokurtic

Gra

in-S

ize

Dis

trib

uti

on

% GRAVEL: 64.27419 58.95149 2.307226 0.836349 0 2.180357

% SAND: 35.07671 38.19612 97.14663 92.67957 69.00474 97.67071

% MUD: 0.649107 2.85239 0.54614 6.484085 30.99526 0.148931

% V

COARSE

GRAVEL:

0 0 0 0 0 0

% COARSE

GRAVEL:

0 0 0 0 0 0

% MEDIUM

GRAVEL:

0 0 0 0 0 0

% FINE

GRAVEL:

31.40244 38.07979 0.479066 0.301086 0 0.316503

% V FINE

GRAVEL:

32.87175 20.8717 1.82816 0.535264 0 1.863853

% V

COARSE

SAND:

20.9546 11.60692 9.572144 1.049238 0.026961 4.92841

% COARSE

SAND:

7.912738 8.196829 36.71555 4.458502 0.164764 11.28862

% MEDIUM

SAND:

3.664942 8.786633 40.1406 27.14029 2.162907 36.02612

% FINE

SAND:

1.658895 6.07012 9.254603 41.40385 18.49256 43.6624

% V FINE

SAND:

0.885531 3.535619 1.463735 18.62768 48.15755 1.765161

% V

COARSE

SILT:

0.649107 2.85239 0.54614 6.484085 30.99526 0.148931

101

Appendix D

Petrographic and Geochemical Figures/Tables

102

Figure D 1. Quartz-Alkali feldspar-Plagioclase (QAP) plutonic compositional classification diagram

plotting bedrock and saprolite samples.

103

Figure D 2. Elemental abundances of Cr, Sc, Co, and FeO across average bedrock and channel sediments.

104

Figure D 3. Cr/Th vs Th/Sc iterative plots of CD-1 (above) and CD-3 (below).

105

Table D 1. Descriptive compositional parameters and ratios for Stepladder bedrock and saprolite samples.

A/CNK A/NK ASI Fe* N+K-Ca

Bedrock

ST09-02 1.47 1.83 1.49 0.75 6.30

CF00-18 1.45 1.86 1.48 0.71 5.84

CF96-4 1.47 1.82 1.49 0.77 6.42

CF96-8 1.52 1.90 1.54 0.73 5.85

Avg 1.48 1.85 1.50 0.74 6.11

Saprolite

CF00-04 1.43 1.74 1.44 0.81 6.49

CF00-05 1.45 1.77 1.47 0.78 6.36

Avg 1.43 1.75 1.46 0.80 6.43

Formulas:

A/CNK: Al2O3/CaO+Na2O+K2O

A/NK: Al2O3/ Na2O+K2O

ASI: Al/Ca – 1.67P + Na + K

Fe*: Fe* FeOtot/ FeOtot + MgO

N+K-Ca: Na2O + K2O – CaO

106

Table D 2. Trace element ratios of Stepladder channel sediments, magnetite concentrate, bedrock, and saprolite.

*Data from Modi (2011)

Note: Cr values used for samples CD-1 and CD-3 were derived from Modi (2011) from samples with respective grain-size

distributions.

Sediment Samples Bedrock* Saprolite*

CD-1

Avg.

CD-2 CD-3 CD-4 CD-5 Avg. Avg.

Th/Sc 4.29 3.86 4.52 2.31 1.36 10.66 9.11

La/Sc 15.68 11.64 7.55 7.67 5.89 35.06 32.36

La/Th 3.65 3.02 1.67 3.33 4.27 3.29 3.55

Zr/Sc 72.86 57.86 44.50 39.03 42.93 274.52 207.54

Th/Co 6.00 3.60 6.03 2.38 1.41 5.46 4.86

Co/Th 0.17 0.28 0.16 0.42 0.71 0.18 0.20

Cr/Th 0.83 1.20 0.28 2.24 2.03 0.23 0.23

107

VITA

Forrest Christopher Driscoll was born on July 17th, 1992 in Radford, Virginia.

During high school, he attended the Southwest Virginia Governor’s School for Science,

Mathematics, and Technology. In 2010, he enrolled at Virginia Tech to pursue his

interest in geology. While at Virginia Tech, he was an active research assistant for other

graduate students. In 2014, he graduated from Virginia Tech with a B.S. in geology.

Because of his positive experience doing research, he enrolled as a graduate student in

the Department Earth and Planetary Sciences at the University of Tennessee, Knoxville

to work with advisor Dr. Chris Fedo. He defended his thesis on July 8th, 2016 to receive

his M.S. in Geology.